Sandboxaq

About SandboxAQ SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact. The Opportunity The SandboxAQ AI team is looking for a hands-on Manager, AI Engineering to help us build the future of agentic collaboration, trust and ROI. Our goal is to make agents work well on their own, in teams, and with humans. This includes the following aspects: - Security: Discovery of agents, evaluation, red teaming, monitoring, guardrails, etc. - Quality: Measuring ROI of agents and suggesting improvements - Collaboration: Bringing humans and agents together into one place with shared context A successful candidate thrives at the intersection of AI and software engineering. You deeply understand how models and agents work, how they can fail, how they can be protected and improved. You have hands-on experience with agents in production, know what works and what doesn’t, know the latest trends and you’re opinionated about the future. You know what you don’t know and enjoy learning to close those gaps. You’ll turn your insights and innovation into real world features baked into our platform - shipping code to production. This is a hands-on leadership role where you’ll break things, fix them and then harden them for good while also leading a small team of engineers. At the same time, you’ll have freedom to explore, collaborate, publish, and deploy, shaping the field of agentic collaboration and trust from all angles. You will help set technical direction, raise the quality bar, mentor team members, and ensure that the team moves quickly from research insight to real-world product impact. We’re looking for somebody with the curiosity of a researcher, the rigor of an engineer, and the creativity of a hacker. You will be part of a diverse team consisting of ML experts, security experts, mathematicians, and software engineers, each playing a key role in efficient and effective enablement of the cutting-edge technologies being developed at SandboxAQ. Key Responsibilities - Lead and grow a small, highly technical team while remaining deeply involved in hands-on engineering and research. - Set technical direction, break down ambiguous problems, establish practical plans for fast, high-quality execution, and build a culture of ownership, low-ego collaboration, thoughtful experimentation, and high standards. - Create new agentic capabilities, including frameworks for monitoring, guardrailing, and evaluating agents, while staying current on the latest agentic developments and identifying new opportunities. - Perform classical ML tasks, including exploratory data analysis, feature engineering, and model fine-tuning, and rapidly iterate on prototypes and features based on feedback and evolving product needs. - Work closely with Product and Research to translate AI research into applicable features and software engineering projects. - Contribute production-ready code and technical designs, working across engineering to deliver scalable, reliable software. Essential Skills & Experience - BSc in Computer Science or related field with exposure to AI/ML. - Deep expertise in AI/ML, software engineering, or AI security. - Strong programming skills in Python, and relevant ML and/or agentic frameworks. - Demonstrated ability to work cross-functionally and collaboratively with a high degree of end-to-end ownership, delivering real world outcomes. - Ability to pick up other programming languages and technologies as required to ship scalable and reliable software. Highly Desired Skills & Experience - PhD in Computer Science or related field with focus on AI/ML or similar. - Hands-on experience with at least one of the following: agent orchestration, agent harnesses, agent teams, jailbreaking / prompt injection, red teaming, data poisoning or evasion attacks, secure model deployment or sandboxing, detection and monitoring for AI misuse. - Experience contributing to open source projects. - Experience in a fast-paced startup environment. - Experience in cybersecurity is a plus, but not essential. Why Join Us? We offer a comprehensive and competitive benefits package designed to support your health, financial well-being, and life outside of work. - Career Defining Work : Your work will directly accelerate the discovery of better drugs and better materials, advance human health, and enable safer and more sustainable technologies by helping customers put AI Simulation capabilities into real world use. - Compensation: Competitive base salary, performance-based incentives or bonuses (where applicable), and equity participation. - Benefits: Comprehensive medical, dental, and vision coverage for employees and dependents with generous employer premium contributions, retirement savings with company matching, paid parental leave, and inclusive family-building benefits. - Work-Life Balance: Fully remote, Flexible paid time off, company-wide seasonal breaks, and support for flexible work arrangements that enable sustainable performance. - Learning and Growth: Opportunities for continuous learning and growth through on-the-job development, cross-functional collaboration, and access to internal learning and development programs. SandboxAQ Welcomes All We are committed to fostering a culture of belonging and respect, where diverse perspectives are actively sought and valued. Our multidisciplinary environment provides ample opportunity for continuous growth - working alongside humble, empowered, and ambitious colleagues ready to tackle epic challenges. Equal Employment Opportunity : All qualified applicants will receive consideration regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. Accommodations : We provide reasonable accommodations for individuals with disabilities in job application procedures for open roles. If you need such an accommodation, please let a member of our Recruiting team know. Read: Guidance for candidates on using AI Tools in interviews

About SandboxAQ SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact. The Opportunity The SandboxAQ AI team is looking for an AI Engineer to help us build the future of agentic collaboration, trust and ROI. Our goal is to make agents work well on their own, in teams, and with humans. This includes the following aspects: - Security: Discovery of agents, evaluation, red teaming, monitoring, guardrails, etc. - Quality: Measuring ROI of agents and suggesting improvements - Collaboration: Bringing humans and agents together into one place with shared context A successful candidate thrives at the intersection of AI and software engineering. You deeply understand how models and agents work, how they can fail, how they can be protected and improved. You have hands-on experience with agents in production, know what works and what doesn’t, know the latest trends and you’re opinionated about the future. You know what you don’t know and enjoy learning to close those gaps. You’ll turn your insights and innovation into real world features baked into our platform - shipping code to production. This is a hands-on role where you’ll break things, fix them and then harden them for good. At the same time, you’ll have freedom to explore, collaborate, publish, and deploy, shaping the field of agentic collaboration and trust from all angles. We’re looking for somebody with the curiosity of a researcher, the rigor of an engineer, and the creativity of a hacker. You will be part of a diverse team consisting of ML experts, security experts, mathematicians, and software engineers, each playing a key role in efficient and effective enablement of the cutting-edge technologies being developed at SandboxAQ. Key Responsibilities - Create new agentic capabilities - frameworks for monitoring, guardrailing, and evaluating them, and to make them work together more effectively. - Perform classical ML tasks - exploratory data analysis, feature engineering and fine-tuning models using the latest frameworks. - Work closely with Product and Research to translate AI research into applicable features and software engineering projects. - Rapidly iterate on prototypes and features based on feedback and evolving product needs. - Contribute production ready code, working across engineering to deliver scalable software. - Stay on the edge of the latest agentic developments and explore new opportunities. Essential Skills & Experience - MSc in Computer Science or related field with exposure to AI/ML. - Deep expertise in AI/ML, software engineering, or AI security. - Strong programming skills in Python, and relevant ML and/or agentic frameworks. - Demonstrated ability to work cross-functionally and collaboratively with a high degree of end-to-end ownership, delivering real world outcomes. - Ability to pick up other programming languages and technologies as required to ship scalable and reliable software. Highly Desired Skills & Experience - PhD in Computer Science or related field with focus on AI/ML or similar. - Hands-on experience with at least one of the following: agent orchestration, agent harnesses, agent teams, jailbreaking / prompt injection, red teaming, data poisoning or evasion attacks, secure model deployment or sandboxing, detection and monitoring for AI misuse. - Experience contributing to open source projects. - Experience in a fast-paced startup environment. - Experience in cybersecurity is a plus, but not essential. Why Join Us? We offer competitive compensation, a comprehensive benefits package, and opportunities for professional growth. - Compensation: Competitive base salary, performance-based incentives or bonuses (where applicable), and equity participation. - Benefits: Comprehensive medical, dental, and vision coverage for employees and dependents with generous employer premium contributions, retirement savings with company matching, paid parental leave, and inclusive family-building benefits. - Work-Life Balance: Flexible paid time off, company-wide seasonal breaks, and support for flexible work arrangements that enable sustainable performance. - Career Development: Opportunities for continuous learning and growth through on-the-job development, cross-functional collaboration, and access to internal learning and development programs. SandboxAQ Welcomes All We are committed to fostering a culture of belonging and respect, where diverse perspectives are actively sought and valued. Our multidisciplinary environment provides ample opportunity for continuous growth - working alongside humble, empowered, and ambitious colleagues ready to tackle epic challenges. Equal Employment Opportunity : All qualified applicants will receive consideration regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. Accommodations : We provide reasonable accommodations for individuals with disabilities in job application procedures for open roles. If you need such an accommodation, please let a member of our Recruiting team know. Read: Guidance for candidates on using AI Tools in interviews

About SandboxAQ SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact. The Opportunity Introduction to the team: The AI Simulation (AI Sim) division at SandboxAQ applies physics and AI simulation to problems in drug discovery and the material sciences. You will work within a highly skilled, multidisciplinary team of computational chemists, physicists, AI experts, and software engineers, on a generative platform that is used across both application areas. Introduction to the role: We are looking for a Machine Learning Scientist to help build the generative engine at the centre of SandboxAQ's material discovery work. The platform finds compounds that match a desired property profile by navigating chemical space while balancing multiple competing objectives. You will: (1) implement, extend, and optimise frontier generative architectures for material discovery; (2) own the interface between the generative engine and the property predictors that supply its reward signal; (3) identify, ingest, and quality-control the data these models are trained and evaluated on; and (4) turn the models you build into production capability that discovery scientists across the company can run. See how SandboxAQ is helping build America's semiconductor supply chain from the materials up Key Responsibilities - Architect and evolve our flagship generative platform , serving as a core contributor to the engine that will redefine how the industry discovers new materials. - Implement and optimize state-of-the-art generative models - including diffusion, flow-matching, and GFlowNets, or LLM- and agent-based methods — to navigate high-dimensional chemical space and solve the multi-objective optimization problems that material discovery presents. - Own the reward interface. Integrate learned surrogates, and simulation-derived oracles as the objective signal driving generation, and design reward formulations that hold up when several objectives are in genuine tension e.g. performance against environmental and safety constraints. - Develop and deploy computational methods and workflows to generate and evaluate hypotheses, guiding design decisions and influencing project direction. - Identify relevant data sources and take responsibility for data ingestion, QC, and validation. - Collaborate daily with a core group of ML researchers to implement frontier generative architectures, while working closely with the broader R&D, discovery, engineering, and product teams. Essential Skills & Experience - Hands-on expertise building and shipping modern generative or applied ML for material discovery with at least 4+ years of experience delivering these solutions in industry or an equivalent research setting. - Demonstrated ability to write clean, maintainable, and robust production-grade code designed for industry-scale applications. - Proven ability to build scalable ML, e.g. using PyTorch, TensorFlow, or JAX. - Familiarity with cloud-based platforms (e.g. Google Cloud Platform, AWS) for compute and data processing and storage. - PhD or MSc in Computational Chemistry, Physics, Computer Science, or equivalent. - Excellent communication skills and a record of fostering successful internal collaboration in a fast-paced environment. - Experience developing ML code in a collaborative environment using modern software engineering best practices. Highly Desired Skills & Experience We are growing this team across three areas of generative expertise, listed in the order we most need them. You do not need all three — deep, hands-on strength in any one of them is what we are looking for. - Active learning and bayesian optimization. Driving a design-make-test loop with an expensive oracle such as a physics simulation (DFT, molecular dynamics) or an experimental lab-in-the-loop assay. - Guided generative modeling for material discovery; generation constrained to makeable chemical space; inference-time steering (guided diffusion, sequential monte-carlo and related approaches) or fine-tuning (LoRA, reinforcement learning) for adapting general models to a particular domain of interest;. - Agentic and LLM approaches to material discovery. Why Join Us? We offer competitive compensation, a comprehensive benefits package, and opportunities for professional growth. - Compensation: Competitive base salary commensurate with experience, plus equity and performance-based incentives. - Benefits: Comprehensive health, dental, and vision insurance; 401(k) with company match; generous parental leave. - Work-Life Balance: Flexible hybrid work arrangements, generous PTO, and a culture that respects focus time and recovery. - Career Development: Direct exposure to CHIPS Act-funded programs, senior scientific and executive leadership, mentorship, and dedicated learning budgets to support continued growth. SandboxAQ Welcomes All We are committed to fostering a culture of belonging and respect, where diverse perspectives are actively sought and valued. Our multidisciplinary environment provides ample opportunity for continuous growth - working alongside humble, empowered, and ambitious colleagues ready to tackle epic challenges. Equal Employment Opportunity : All qualified applicants will receive consideration regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. Accommodations : We provide reasonable accommodations for individuals with disabilities in job application procedures for open roles. If you need such an accommodation, please let a member of our Recruiting team know. Read: Guidance for candidates on using AI Tools in interviews

About SandboxAQ SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact. The Opportunity Introduction to the team: This role is for the PFAS team which sits within SandboxAQ's Chemical Simulation (ChemSim) group. Our mission is to develop PFAS-lean or PFAS-free substitutes and formulations for semiconductor process and fab materials that meet both performance specifications and environmental and safety requirements in complex semiconductor manufacturing environments. We combine generative ML, physics based simulation (e.g. DFT and molecular dynamics), Large Quantitative Models for property prediction, and multi-scale modeling with a partner driven experimental validation loop. You will work alongside industrial co-development partners to move candidate molecules from prediction to qualified use. Introduction to the role: The PFAS team is hiring Machine Learning Scientists to own machine learned force fields (MLFFs) for the PFAS substitution programme, including generating the first principles data they are trained on. Machine learned potentials are the load bearing element of our discovery pipeline: the properties that decide whether a candidate molecule can replace a PFAS incumbent — among them reactivity, thermal stability, and the diffusivity through polymer matrices — are ones that the physics based simulations can compute accurately but far too slowly to screen a library, and that classical force fields compute quickly but may not be accurate enough to trust. In this role you will: (1) design and run the high-throughput quantum chemistry and molecular dynamics campaigns that produce our training data, and own the infrastructure that makes them reproducible; (2) train, validate, and deploy the potentials that data supports, and identify where each model's domain of validity ends; and (3) extend machine learned potentials into the chemistry that PFAS substitution requires. See how SandboxAQ is helping build America's semiconductor supply chain from the materials up Key Responsibilities - Own the training data. Design and run high-throughput physics based simulation campaigns that produce labelled training data for the PFAS chemical space, making the calls that determine whether the data is fit to train on — level of theory, basis set, convergence criteria, sampling strategy, and error budget. - Build the data generation infrastructure. Stand up automated, restartable, provenance tracked workflows across cloud and HPC by collaborating with the engineering team; curate and version the resulting datasets, and combine internally generated first-principles data with relevant public molecular and materials datasets under consistent conventions. - Train and own the MLFF stack for the PFAS vertical . Select architectures, train, validate, and deploy machine learned interatomic potentials across the chemical space of PFAS substitution demands. Fine tuning universal or foundation potentials, or training from scratch when appropriate. - Deliver the property predictions the screening pipeline runs on. Build and validate MLFF-driven protocols for the properties our pipelines need — for example protonation and deprotonation energetics underpinning pKa, ion diffusivity in glassy polymer matrices, and Green-Kubo viscosity and thermal conductivity — each benchmarked against reference data or experiment. - Push the potentials into the process chemistries that matter. Extend coverage to resin phase polymerisation and plasma surface etch chemistry, moving beyond single molecule, gas phase behaviour into the condensed phase regime our applications actually occupy. - Run production campaigns and deploy models on our platform . Execute at scale prediction campaigns across full candidate libraries, and land trained models, datasets, and reproducible training pipelines in SandboxAQ tooling so that other scientists can run them from written documentation. - Collaborate across the discovery loop, and set the honesty bar . Partner with the generative modeling, molecular property ML, and simulation teams so that MLFF-derived properties are usable as screening oracles and reward signals. Work with our partner facing materials scientists so predictions are checked against real process constraints. Report error bars, hold-out performance, and domain-of-validity limits alongside every predicted property, and escalate when a model is being asked a question it cannot answer. Essential Skills & Experience - PhD in Computational Chemistry, Materials Science, Physics, Machine Learning, or a related field, with deep specialization in machine learned interatomic potentials or atomistic simulation. - Demonstrated depth developing and deploying machine learned force fields — including at least one potential that you trained, validated, and put into the hands of other people who now rely on it, whether inside a company or as a public release. We are interested in what you have built and shipped rather than in years served, and this posting is open across experience levels. - Hands-on experience generating first principles training data at throughput with production quantum chemistry and electronic structure codes (e.g. VASP, Quantum ESPRESSO, CP2K, ORCA, Psi4, or Gaussian), including the judgment to set and defend level of theory, basis set, and convergence criteria. - Demonstrated fluency with descriptor based, modern equivariant, and message-passing potential architectures (e.g. MACE, NequIP, Allegro, TensorNet, DeePMD, ANI-class, or FairChem/UMA-family models) — including what each is good for and where each fails. - Strong programming skills in Python and hands on experience with modern ML frameworks (e.g. PyTorch, JAX), including training at scale on GPU clusters. - Practical experience coupling learned potentials into production molecular dynamics engines (e.g. LAMMPS, GROMACS, OpenMM, ASE) and extracting converged physical observables from the resulting trajectories. - Hands-on experience with classical molecular dynamics in those same engines — force field selection and parameterisation for organic and condensed phase systems (e.g. OPLS-AA, AMBER/GAFF, or ReaxFF for reactive chemistry), system construction and equilibration, ensemble and thermostat/barostat choice, and the judgment to say when a classical description stops being trustworthy and a learned potential is required. - Experience building automated computational workflows and curating large scientific datasets — provenance, versioning, and reproducibility. - Demonstrated validation discipline: a track record of characterising model error and out-of-domain failure rather than reporting best case benchmark numbers. - Experience working in cloud and high performance computing environments. Highly Desired Skills & Experience - Hands-on experience with fluorine containing chemistry, fluoropolymers, or PFAS-adjacent molecular systems. - Experience computing free energies by thermodynamic cycle or alchemical methods, and/or transport properties by Green-Kubo or non-equilibrium MD. - Experience with long range electrostatics, polarization, or implicit solvation treatments in learned potentials. - Familiarity with generative molecular design frameworks Why Join Us? We offer competitive compensation, a comprehensive benefits package, and opportunities for professional growth. - Compensation: Competitive base salary commensurate with experience, plus equity and performance-based incentives. - Benefits: Comprehensive health, dental, and vision insurance; 401(k) with company match; generous parental leave. - Work-Life Balance: Flexible hybrid work arrangements, generous PTO, and a culture that respects focus time and recovery. - Career Development: Direct exposure to CHIPS Act-funded programs, senior scientific and executive leadership, mentorship, and dedicated learning budgets to support continued growth. SandboxAQ Welcomes All We are committed to fostering a culture of belonging and respect, where diverse perspectives are actively sought and valued. Our multidisciplinary environment provides ample opportunity for continuous growth - working alongside humble, empowered, and ambitious colleagues ready to tackle epic challenges. Equal Employment Opportunity : All qualified applicants will receive consideration regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. Accommodations : We provide reasonable accommodations for individuals with disabilities in job application procedures for open roles. If you need such an accommodation, please let a member of our Recruiting team know. Read: Guidance for candidates on using AI Tools in interviews

About SandboxAQ SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact. The Opportunity The SandboxAQ AI team is looking for an AI Engineer to help us build the future of agentic collaboration, trust and ROI. Our goal is to make agents work well on their own, in teams, and with humans. This includes the following aspects: - Security: Discovery of agents, evaluation, red teaming, monitoring, guardrails, etc. - Quality: Measuring ROI of agents and suggesting improvements - Collaboration: Bringing humans and agents together into one place with shared context A successful candidate thrives at the intersection of AI and software engineering. You deeply understand how models and agents work, how they can fail, how they can be protected and improved. You have hands-on experience with agents in production, know what works and what doesn’t, know the latest trends and you’re opinionated about the future. You know what you don’t know and enjoy learning to close those gaps. You’ll turn your insights and innovation into real world features baked into our platform - shipping code to production. This is a hands-on role where you’ll break things, fix them and then harden them for good. At the same time, you’ll have freedom to explore, collaborate, publish, and deploy, shaping the field of agentic collaboration and trust from all angles. We’re looking for somebody with the curiosity of a researcher, the rigor of an engineer, and the creativity of a hacker. You will be part of a diverse team consisting of ML experts, security experts, mathematicians, and software engineers, each playing a key role in efficient and effective enablement of the cutting-edge technologies being developed at SandboxAQ. Key Responsibilities - Create new agentic capabilities - frameworks for monitoring, guardrailing, and evaluating them, and to make them work together more effectively. - Perform classical ML tasks - exploratory data analysis, feature engineering and fine-tuning models using the latest frameworks. - Work closely with Product and Research to translate AI research into applicable features and software engineering projects. - Rapidly iterate on prototypes and features based on feedback and evolving product needs. - Contribute production ready code, working across engineering to deliver scalable software. - Stay on the edge of the latest agentic developments and explore new opportunities. Essential Skills & Experience - MSc in Computer Science or related field with exposure to AI/ML. - Deep expertise in AI/ML, software engineering, or AI security. - Strong programming skills in Python, and relevant ML and/or agentic frameworks. - Demonstrated ability to work cross-functionally and collaboratively with a high degree of end-to-end ownership, delivering real world outcomes. - Ability to pick up other programming languages and technologies as required to ship scalable and reliable software. Highly Desired Skills & Experience - PhD in Computer Science or related field with focus on AI/ML or similar. - Hands-on experience with at least one of the following: agent orchestration, agent harnesses, agent teams, jailbreaking / prompt injection, red teaming, data poisoning or evasion attacks, secure model deployment or sandboxing, detection and monitoring for AI misuse. - Experience contributing to open source projects. - Experience in a fast-paced startup environment. - Experience in cybersecurity is a plus, but not essential. Why Join Us? We offer competitive compensation, a comprehensive benefits package, and opportunities for professional growth. - Compensation: Competitive base salary, performance-based incentives or bonuses (where applicable), and equity participation. - Benefits: Comprehensive medical, dental, and vision coverage for employees and dependents with generous employer premium contributions, retirement savings with company matching, paid parental leave, and inclusive family-building benefits. - Work-Life Balance: Flexible paid time off, company-wide seasonal breaks, and support for flexible work arrangements that enable sustainable performance. - Career Development: Opportunities for continuous learning and growth through on-the-job development, cross-functional collaboration, and access to internal learning and development programs. SandboxAQ Welcomes All We are committed to fostering a culture of belonging and respect, where diverse perspectives are actively sought and valued. Our multidisciplinary environment provides ample opportunity for continuous growth - working alongside humble, empowered, and ambitious colleagues ready to tackle epic challenges. Equal Employment Opportunity : All qualified applicants will receive consideration regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. Accommodations : We provide reasonable accommodations for individuals with disabilities in job application procedures for open roles. If you need such an accommodation, please let a member of our Recruiting team know. Read: Guidance for candidates on using AI Tools in interviews

About SandboxAQ SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact. The Opportunity The SandboxAQ AI team is looking for a hands-on Manager, AI Engineering to help us build the future of agentic collaboration, trust and ROI. Our goal is to make agents work well on their own, in teams, and with humans. This includes the following aspects: - Security: Discovery of agents, evaluation, red teaming, monitoring, guardrails, etc. - Quality: Measuring ROI of agents and suggesting improvements - Collaboration: Bringing humans and agents together into one place with shared context A successful candidate thrives at the intersection of AI and software engineering. You deeply understand how models and agents work, how they can fail, how they can be protected and improved. You have hands-on experience with agents in production, know what works and what doesn’t, know the latest trends and you’re opinionated about the future. You know what you don’t know and enjoy learning to close those gaps. You’ll turn your insights and innovation into real world features baked into our platform - shipping code to production. This is a hands-on leadership role where you’ll break things, fix them and then harden them for good while also leading a small team of engineers. At the same time, you’ll have freedom to explore, collaborate, publish, and deploy, shaping the field of agentic collaboration and trust from all angles. You will help set technical direction, raise the quality bar, mentor team members, and ensure that the team moves quickly from research insight to real-world product impact. We’re looking for somebody with the curiosity of a researcher, the rigor of an engineer, and the creativity of a hacker. You will be part of a diverse team consisting of ML experts, security experts, mathematicians, and software engineers, each playing a key role in efficient and effective enablement of the cutting-edge technologies being developed at SandboxAQ. Key Responsibilities - Lead and grow a small, highly technical team while remaining deeply involved in hands-on engineering and research. - Set technical direction, break down ambiguous problems, establish practical plans for fast, high-quality execution, and build a culture of ownership, low-ego collaboration, thoughtful experimentation, and high standards. - Create new agentic capabilities, including frameworks for monitoring, guardrailing, and evaluating agents, while staying current on the latest agentic developments and identifying new opportunities. - Perform classical ML tasks, including exploratory data analysis, feature engineering, and model fine-tuning, and rapidly iterate on prototypes and features based on feedback and evolving product needs. - Work closely with Product and Research to translate AI research into applicable features and software engineering projects. - Contribute production-ready code and technical designs, working across engineering to deliver scalable, reliable software. Essential Skills & Experience - BSc in Computer Science or related field with exposure to AI/ML. - Deep expertise in AI/ML, software engineering, or AI security. - Strong programming skills in Python, and relevant ML and/or agentic frameworks. - Demonstrated ability to work cross-functionally and collaboratively with a high degree of end-to-end ownership, delivering real world outcomes. - Ability to pick up other programming languages and technologies as required to ship scalable and reliable software. Highly Desired Skills & Experience - PhD in Computer Science or related field with focus on AI/ML or similar. - Hands-on experience with at least one of the following: agent orchestration, agent harnesses, agent teams, jailbreaking / prompt injection, red teaming, data poisoning or evasion attacks, secure model deployment or sandboxing, detection and monitoring for AI misuse. - Experience contributing to open source projects. - Experience in a fast-paced startup environment. - Experience in cybersecurity is a plus, but not essential. Why Join Us? We offer a comprehensive and competitive benefits package designed to support your health, financial well-being, and life outside of work. - Career Defining Work : Your work will directly accelerate the discovery of better drugs and better materials, advance human health, and enable safer and more sustainable technologies by helping customers put AI Simulation capabilities into real world use. - Compensation: Competitive base salary, performance-based incentives or bonuses (where applicable), and equity participation. - Benefits: Comprehensive medical, dental, and vision coverage for employees and dependents with generous employer premium contributions, retirement savings with company matching, paid parental leave, and inclusive family-building benefits. - Work-Life Balance: Fully remote, Flexible paid time off, company-wide seasonal breaks, and support for flexible work arrangements that enable sustainable performance. - Learning and Growth: Opportunities for continuous learning and growth through on-the-job development, cross-functional collaboration, and access to internal learning and development programs. SandboxAQ Welcomes All We are committed to fostering a culture of belonging and respect, where diverse perspectives are actively sought and valued. Our multidisciplinary environment provides ample opportunity for continuous growth - working alongside humble, empowered, and ambitious colleagues ready to tackle epic challenges. Equal Employment Opportunity : All qualified applicants will receive consideration regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. Accommodations : We provide reasonable accommodations for individuals with disabilities in job application procedures for open roles. If you need such an accommodation, please let a member of our Recruiting team know. Read: Guidance for candidates on using AI Tools in interviews

ABOUT SANDBOXAQ SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact. THE OPPORTUNITY SandboxAQ’s AI Simulation (AISim) division develops and applies Large Quantitative Models (LQMs) that are grounded in physics, chemistry, mathematics and biology to simulate molecular behavior with scientific precision and accelerate discovery in the physical world across biopharma, chemicals, advanced materials, healthcare, and so much more. The AISim division is looking for a seasoned Senior Director of Product Management reporting to the Vice President of Product to own the product strategy and roadmap for the shared platform foundation that underpins both the BioSim and ChemSim businesses. This senior leadership role involves building, growing, and managing a team of 5-6 PM ICs across ML Platform, Data, Agentic, Core Infrastructure, Trust, and Partner integrations, while remaining directly involved in day-to-day execution until the team is fully ramped. This role will drive end-to-end platform strategy, vision, and execution, including critical build-vs-buy decisions. Additionally, they will establish data-driven operating rhythms, define metrics to measure success, and be accountable for platform OKRs. KEY RESPONSIBILITIES - Set and own end-to-end platform strategy, vision, and roadmap across BioSim and ChemSim, including build-vs-buy decisions. - Hire, grow, and lead a team of 5-6 PM ICs across ML Platform, Data, Agentic, Core Infrastructure, Trust, and Partner Integrations — driving key deliverables personally until the team is fully ramped. - Balance competing internal and external customer needs across several distinct domains. - Establish a data-driven operating rhythm: define the metrics that matter, present them in business reviews, bridge variances to OKRs, and drive course corrections. ESSENTIAL SKILLS & EXPERIENCE - 10+ years in product management, including 5+ years managing individual contributors. - Strong platform or infrastructure product background — e.g., MLOps, data platforms, scientific engines, or developer tools. - A track record of building and shipping enterprise-grade commercial platforms. - Experience with multi-tenant SaaS and enterprise security/compliance (e.g., HIPAA, SOC 2, FedRAMP) and API governance. - Demonstrated ability to thrive in ambiguous, fast-moving environments and turn unclear customer problems into scalable products. - Bachelor's degree in Computer Science, Engineering, or equivalent practical experience. HIGHLY DESIRED SKILLS & EXPERIENCE - MBA or equivalent business leadership experience. - Familiarity with AI/ML platform requirements across inference, training, fine-tuning, agentic AI, and federated learning. - Deep domain expertise in scientific simulation software for drug discovery and/or materials research. - PhD in Computational Chemistry, Computational Biology, or Biomedical Engineering. - Physically located in the Greater Seattle Metropolitan area or SF Bay Area WHY JOIN US? We offer a comprehensive and competitive benefits package designed to support your hea

ABOUT SANDBOXAQ SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact. THE OPPORTUNITY Introduction to the team: The Magnets team is one of several research verticals within SandboxAQ's broader Chemical Simulation group, which uses advanced computational methods, physics-based simulation, and AI to discover and develop novel materials. Within that effort, the Magnets vertical is focused on one of the most strategically important materials problems today: developing high-performance permanent magnets that reduce or eliminate reliance on neodymium and other rare earth elements and can be manufactured in the United States. Our goal is to create novel magnet formulations that use existing industry processes and equipment while matching or exceeding the performance of today's leading NdFeB magnets in demanding applications such as semiconductor equipment, vacuum systems, precision motion devices, and defense technologies. Introduction to the role: We are seeking a Research Scientist to help drive the computational discovery and optimization of next-generation magnet materials. The ideal candidate has a strong background in applying first-principles and multi-scale reference systems, computational simulation, together with machine learning, to magnetic and intermetallic materials. In this role you will (1) run and interpret atomistic and multi-scale simulations that predict the properties of magnets materials, (2) build and deploy computational and ML-driven workflows that screen rare-earth-lean and rare-earth-free candidates at scale, (3) work with experimental collaborators to test and refine predictions against real-world data, and (4) contribute to the project plans, publications, and IP of the vertical. You will report to the Chief Scientist, Magnets and work closely with our AI simulation platform and data-generation teams. KEY RESPONSIBILITIES - Execute, analyze, and document DFT and multi-scale reference systems to predict phase stability, magnetocrystalline anisotropy, saturation magnetization, Curie temperature, and other properties across Fe- and Co-based intermetallic systems using U.S.-accessible alloying elements. - Develop and test computational workflows and ML interatomic potentials / surrogate models that enable high-throughput screening and optimization of rare-earth-lean and rare-earth-free permanent magnet candidates. - Lead high-fidelity data generation campaigns that feed the magnetism-aware LQM; work with platform and data-generation teams to specify the energetics, descriptors, and uncertainty estimates the workflows require. - Connect atomistic simulation outputs to microstructure- and process-level predictions (powder metallurgy, sintering, heat treatment) to keep candidate formulations manufacturable with existing industry equipment. - Collaborate with experimental validation partners to test and iterate on model predictions, contributing to the Design-Build-Test-Learn (DBTL) feedback loop between computation and the lab, ensuring that LQM models are more accurate over time. - Work within defined projects, deliverables and milestones alongside agile, multidisciplinary teams, and generate and evaluate hypotheses that influence project direction. - Communicate research findings through scientific talks, peer-reviewed publications, patents, and partner-facing technical presentations; support junior scientists and interns as the team grows. ESSENTIAL SKILLS & EXPERIENCE - PhD or equivalent experience in Solid- state Physics, Quantum Chemistry applied to Materials Science or a related field. - Hands-on experience with DFT or atomistic simulation. - Strong programming skills in Python and modern scientific-computing practices. - Experience applying machine learning, surrogate modeling, or high-throughput methods to materials problems. - Demonstrated ability to collaborate with experimental or cross-functional teams to validate and iterate on predictions. - Because this position supports specific U.S. Government contractual requirements, we can only consider US Persons (Permanent Residents or Citizens) at this time. HIGHLY DESIRED SKILLS & EXPERIENCE - Specialization in alloys, microstructure engineering, magnetism, intermetallics, or hard/functional magnetic materials. - 3+ years of hands-on experience (post-PhD or equivalent) applying DFT and atomistic simulation specifically to magnetic, intermetallic, crystal lattices, energy bands, or phonons for material science. - Proficiency with common DFT and atomistic simulation software (e.g., VASP, Quantum ESPRESSO, LAMMPS, ASE). - Experience developing or using ML interatomic potentials and AI models for materials discovery (e.g., MACE, NequIP, Allegro, or FairChem) with modern deep learning frameworks (e.g., PyTorch, JAX), and familiarity with HPC and cloud environments. - Hands-on experience with Fe-N, Mn-based, Sm-Co, or other rare-earth-lean permanent magnet systems and their bulk processing challenges. - Experience with finite-temperature magnetism and coercivity modeling, including atomistic spin dynamics and/or micromagnetic simulation. - Familiarity linking composition and microstructure to processing (powder metallurgy, sintering, heat treatment) and to application requirements such as force density, thermal operating envelope, and demagnetization margin. - Familiarity with Bayesian optimization, active learning, or autonomous discovery workflows applied to materials. - Authorship of publications in high-impact peer-reviewed journals, and/or patents, in magnetic materials, computational chemistry, or AI for materials science. - Experience operating within CHIPS Act, DOD, DOE, or other federally funded R&D programs, including awareness of export-control and IP considerations. WHY JOIN US? We offer competitive compensation, a comprehensive benefits package, and opportunities for professional growth. - Compensation: Competitive base salary commensurate with experience, plus equity and performance-based incentives. - Benefits: Comprehensive health, dental, and vision insurance; 401(k) with company match; generous parental leave. - Work-Life Balance: Flexible hybrid work arrangements, generous PTO, and a culture that respects focus time and recovery. - Career Development: Direct exposure to CHIPS Act-funded programs, senior scientific and executive leadership, mentorship, and dedicated learning budgets to support continued growth. SANDBOXAQ WELCOMES ALL We are committed to fostering a culture of belonging and respect, where diverse perspectives are actively sought and valued. Our multidisciplinary environment provides ample opportunity for continuous growth - working alongside humble, empowered, and ambitious colleagues ready to tackle epic challenges. Equal Employment Opportunity: All qualified applicants will receive consideration regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. Accommodations: We provide reasonable accommodations for individuals with disabilities in job application procedures for open roles. If you need such an accommodation, please let a member of our Recruiting team know. Read: Guidance for candidates on using AI Tools in interviews https://www.sandboxaq.com/ai-in-interviews

ABOUT SANDBOXAQ SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact. THE OPPORTUNITY The AI Simulation (AISim) division at SandboxAQ is redefining what’s possible at the frontiers of science through AI-powered simulation. Our AQChemSim and AQBioSim businesses apply quantitative AI and scientific computing to complex challenges across biopharma, chemicals, advanced materials, energy, and beyond.The AISim Marketing team brings the same quantitative rigor to go-to-market, building the systems, programs, and insights that enable the business to scale. This role will sit within Marketing while partnering across the broader company to establish a best-in-class marketing operations and analytics foundation. The AISim Marketing team are looking for a Marketing Operations & Analytics Manager to join our team. In this role, you will be responsible for building our marketing measurement and operations function from the ground up. This is a rare greenfield opportunity to shape how SandboxAQ measures marketing performance, connects marketing activity to pipeline and revenue, and uses data to make better investment decisions. You will own the strategy and execution across our martech stack, marketing analytics, attribution, lifecycle programs, and reporting infrastructure. Working closely with Marketing, RevOps, Sales, Finance, and Product, you will create the systems and insights that turn marketing data into trusted business intelligence. KEY RESPONSIBILITIES - Architect and evolve the martech stack: evaluate, select, implement, and optimize the tools required for marketing automation, data management, measurement, and BI; own the roadmap, integrations, vendor relationships, and reporting infrastructure. - Instrument campaigns and programs across the funnel and develop attribution models that connect marketing activity to pipeline, revenue, and ROI. - Build and maintain reporting that ranges from individual campaign performance to cross-channel and full-funnel views, enabling Marketing and cross-functional leadership to make data-driven investment decisions. - Build, test, and continuously improve nurture and lifecycle programs, including segmentation, triggers, lead scoring, and A/B testing. - Establish data hygiene standards, governance processes, and reliable integrations between marketing systems and Salesforce, while partnering with RevOps, Sales, Finance, and Product on shared definitions and measurement. ESSENTIAL SKILLS & EXPERIENCE - 4–7 years of experience in marketing operations, marketing analytics, RevOps, demand generation operations, or a related function, with hands-on ownership of reporting and campaign infrastructure. Bachelor’s degree in Marketing, Communications, Business, or a related field, or equivalent practical experience. - Hands-on Salesforce and marketing automation experience, including campaign structures, reporting, lifecycle management, and platforms such as Marketo, HubSpot, or Pardot. - Demonstrated experience building or improving multi-touch attribution, funnel measurement, lead scoring, pipeline reporting, and lead-to-revenue processes. - Proven ability to build in a greenfield or highly ambiguous environment, taking ownership from strategy through implementation rather than simply defining requirements. - Strong cross-functional communication skills, with the ability to translate go-to-market questions into clear metrics, reporting, and actionable recommendations for Marketing, RevOps, Sales, Finance, and Product. HIGHLY DESIRED SKILLS & EXPERIENCE - Experience using SQL to query, join, and analyze data across multiple sources. - Basic Python or scripting experience for automation, data wrangling, or workflow optimization. - Experience standing up or significantly evolving a BI platform such as Tableau, Looker, or Power BI and/or a data warehouse such as Snowflake or BigQuery. - Experience in B2B, enterprise, SaaS, or deep-tech marketing, particularly in complex or technical buying environments. - Demonstrated use of AI tools and automation to accelerate analysis, connect disparate data sources, improve workflows, and reduce manual marketing operations work. WHY JOIN US? We offer a comprehensive and competitive benefits package designed to support your health, financial well-being, and life outside of work. - Compensation: Competitive base salary, performance-based incentives or bonuses (where applicable), and equity participation. - Benefits: Comprehensive medical, dental, and vision coverage for employees and dependents with generous employer premium contributions, retirement savings with company matching, paid parental leave, and inclusive family-building benefits. - Work-Life Balance: Flexible paid time off, company-wide seasonal breaks, and support for flexible work arrangements that enable sustainable performance. - Career Development: Opportunities for continuous learning and growth through on-the-job development, cross-functional collaboration, and access to internal learning and development programs. SANDBOXAQ WELCOMES ALL We are committed to fostering a culture of belonging and respect, where diverse perspectives are actively sought and valued. Our multidisciplinary environment provides ample opportunity for continuous growth - working alongside humble, empowered, and ambitious colleagues ready to tackle epic challenges. Equal Employment Opportunity: All qualified applicants will receive consideration regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. Accommodations: We provide reasonable accommodations for individuals with disabilities in job application procedures for open roles. If you need such an accommodation, please let a member of our Recruiting team know. Read: Guidance for candidates on using AI Tools in interviews https://www.sandboxaq.com/ai-in-interviews

ABOUT SANDBOXAQ SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact. ABOUT THE TEAM The SandboxAQ AI Generation Engine (SAIGE) team’s mission is to accelerate SandboxAQ’s mission of “Deep Impact at Scale” with a focus on quantitative AI and rapid innovation. More specifically, the SAIGE team aims to: - Build next-generation AI capabilities that establish SandboxAQ as the global pacesetter in quantitative AI. - Identify, incubate, prototype, and launch new AI products for high-potential and longer-term use cases, proving (or disproving) their viability as high-impact, highly profitable business lines. The SAIGE team operates on the following principles: Prototype with Velocity, Explore Boldly, Fail Smart, Learn Fast, Look Forward, and Share Knowledge. Our current top priority use case is leveraging AI and LQMs to solve some of the most impactful problems in the Finance and Insurance industries. THE OPPORTUNITY As the Director of Product Management for the AI Generation Engine (SAIGE), you will be the PM lead for the team and a key partner to engineering, research, and user research. You will: - Own the product strategy and execution for our efforts in Finance & Risk Modeling, partnering closely with financial services and insurance customers to understand their workflows, risk models, and decision-making processes. - Lead rapid prototyping and innovation across a broad range of new ideas and domains, driving 0→1 product discovery, experimentation, and incubation of high-potential use cases. - Operate in a highly ambiguous, fast-changing environment, providing clarity on priorities, making pragmatic trade-offs, and ensuring we ship impactful prototypes and products. This role is ideal for a seasoned product leader who is energized by uncertainty, enjoys working across disciplines (UXR, engineering, research, business), and is excited to build new AI and quantitative products from the ground up. KEY RESPONSIBILITIES LEAD PRODUCT STRATEGY IN FINANCE & RISK MODELING - Own the product vision, roadmap, and execution for our Finance/Risk portfolio, with a focus on financial services and insurance (e.g., portfolio risk, capital modeling, risk analytics, underwriting, and related workflows). - Develop a deep understanding of customer contexts, including current tools, models, and data flows (e.g., portfolio / risk modeling systems, vendor platforms, internal analytics stacks). - Partner with quantitative researchers, ML engineers, and domain experts to translate customer problems into clear product requirements and model/data needs. - Define success metrics and validation strategies to compare our approaches against existing PML/ERM and portfolio views, and to demonstrate differentiated value. DRIVE RAPID PROTOTYPING AND 0→1 INNOVATION - Identify, evaluate, and prioritize new AI / LQM use cases across multiple domains (beyond Finance/Risk), from early signals to clearer opportunities. - Lead 0→1 product discovery: problem framing, hypothesis development, lightweight customer validation, and rapid iteration on prototypes. - Work with engineering and research to scope experiments that are small enough to move quickly but meaningful enough to answer key questions. - Establish and champion a rigorous but pragmatic approach to ruthless prioritization, ensuring the team focuses on the highest-impact opportunities. BUILD STRONG CUSTOMER AND STAKEHOLDER RELATIONSHIPS - Serve as a trusted product partner to senior stakeholders at key customers (e.g., heads of risk, portfolio managers, actuaries, CROs), speaking credibly about risk models, scenarios, and portfolio decisions. - Lead customer conversations from initial discovery through pilot definition and ongoing adoption, connecting customer needs to the SAIGE roadmap. - Communicate progress, learnings, and recommendations clearly to internal and external stakeholders, including executives. ESSENTIAL SKILLS & EXPERIENCE You are a senior product leader who is comfortable at the intersection of AI, quantitative modeling, and financial risk. You thrive in ambiguity, enjoy working closely with deeply technical teams, and can just as easily go deep on models and data as you can on customer needs and business outcomes. You are proactive, low-ego, and collaborative, and you don’t need rigid structure to have impact. - 10+ years of product management experience, with substantial time spent on complex B2B or platform products. - Deep Experience in financial services and/or insurance, especially in one or more of: - Risk modeling (e.g., portfolio risk, capital modeling, asset-liability management, market/credit risk, or insurance risk) - Financial simulation or scenario analysis - Portfolio analytics or decision support tools - Demonstrated ability to work closely with quantitative, engineering, and cross functional teams: - Comfortable discussing models, data pipelines, and trade-offs with engineers and researchers. - Experience working tightly with UXR, design, engineering, and research. - Clear written and verbal communication across technical and non-technical audiences. - Able to translate between technical details and customer/business value. - Proven track record of 0→1 Product Management work: - Identifying new opportunities and shaping them from idea to prototype and early product. - Strong ruthless prioritization skills: can define clear frameworks, make hard trade-offs, and say “no” to good ideas to focus on the best ones. - Demonstrated ability to drive execution without heavy process or structure, and Working through high ambiguity, incomplete information, and changing constraints. - Exceptional customer-facing skills: - Confident leading discovery and roadmap conversations with senior stakeholders. - Skilled at uncovering real needs behind stated requirements and pressure-testing problem statements. - Self-directed, proactive, and comfortable creating structure where needed rather than waiting for it. - Experience in environments with shifting priorities and evolving strategies. - Alignment with SandboxAQ values and the SAIGE principles around rapid prototyping, learning, and communication and shared ownership. HIGHLY DESIRED SKILLS & EXPERIENCE - Direct experience building products involving AI / ML, foundational models, quantitative models, or LLM/agentic systems. - Hands-on exposure to risk tools and vendor platforms (e.g., risk engines, portfolio analytics systems, or modeling platforms used in insurance and financial services). - Experience in both: - A high-growth startup or new product incubation context - A large, complex environment (e.g., Big Tech, major financial institution), giving you a strong sense of how to navigate stakeholders and scale impact. - Educational background in a quantitative or technical field (e.g., computer science, mathematics, physics, statistics, engineering, finance, or similar). If you’re excited by the idea of shaping the future of quantitative AI, building products with real impact in finance and insurance (and possibly other domains), and leading 0→1 innovation in a highly cross-functional team, we’d love to hear from you. WHY JOIN US? We offer a comprehensive and competitive benefits package designed to support your health, financial well-being, and life outside of work. - Compensation: Competitive base salary, performance-based incentives or bonuses (where applicable), and equity participation. - Benefits: Comprehensive medical, dental, and vision coverage for employees and dependents with generous employer premium contributions, retirement savings with company matching, paid parental leave, and inclusive family-building benefits. - Work-Life Balance: Flexible paid time off, company-wide seasonal breaks, and support for flexible work arrangements that enable sustainable performance. - Career Development: Opportunities for continuous learning and growth through on-the-job development, cross-functional collaboration, and access to internal learning and development programs. SANDBOXAQ WELCOMES ALL We are committed to fostering a culture of belonging and respect, where diverse perspectives are actively sought and valued. Our multidisciplinary environment provides ample opportunity for continuous growth - working alongside humble, empowered, and ambitious colleagues ready to tackle epic challenges. Equal Employment Opportunity: All qualified applicants will receive consideration regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. Accommodations: We provide reasonable accommodations for individuals with disabilities in job application procedures for open roles. If you need such an accommodation, please let a member of our Recruiting team know. Read: Guidance for candidates on using AI Tools in interviews https://www.sandboxaq.com/ai-in-interviews

ABOUT SANDBOXAQ SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact. THE OPPORTUNITY Introduction to the team: The PFAS team sits within SandboxAQ's Chemical Simulation (ChemSim) group. Our mission is to develop PFAS-lean or PFAS-free substitutes and formulations for semiconductor process and fab materials that meet both performance specifications and environmental and safety requirements in complex semiconductor manufacturing environments. We combine generative ML, physics-based simulation (e.g. DFT and molecular dynamics), Large Quantitative Models for property prediction, and multi-scale modeling with a partner-driven experimental validation loop — working alongside industrial co-development partners to move candidate molecules from prediction to qualified use. Introduction to the role: The PFAS team is looking for a Staff Materials Research Scientist to serve as the scientific bridge between our generative chemistry discovery workflow and the external partners who validate our candidate molecules. This role is central to our efforts to ensure that the compounds our AI-driven workflow proposes are directionally correct, appropriate for the target semiconductor use case, and grounded in real manufacturing constraints. This person will: (1) own the partner-facing validation loop — serving as the primary point of contact with our co-development partners on problem definition, target specifications, constraints, and qualification criteria; (2) run our generative chemistry workflow, assess the predicted compounds, and rank them by fitness for the use case to deliver decision-ready shortlists for partner validation; (3) translate experimental feedback from partners into concrete technical improvement points that the rest of the team members can act on; and (4) bring semiconductor domain judgment to bear on the whole pipeline, deciding whether workflow outputs are qualitatively and directionally accurate and validating lead molecules against process reality. See how SandboxAQ is helping build America's semiconductor supply chain from the materials up https://www.sandboxaq.com/post/sandboxaq-helping-build-americas-semiconductor-supply-chain KEY RESPONSIBILITIES - Own the partner validation loop. Serve as the primary scientific point of contact between the PFAS team and external co-development partners (e.g. chemical and process-materials suppliers, semiconductor equipment makers, and control/sensor companies), translating partner problems into well-posed target specifications, constraints, and qualification criteria. - Run the discovery workflow and rank candidates. Operate SandboxAQ's generative chemistry discovery workflow for assigned PFAS-substitution use cases; assess the predicted compounds for chemical plausibility and use-case fit, and rank them to produce decision-ready shortlists that partners can take into experimental validation. - Apply semiconductor domain judgment. Evaluate whether generative and simulation outputs are directionally and qualitatively correct for the target application, and validate lead molecules against real-world semiconductor process, performance, and EHS constraints. - Close the experimental feedback loop. Translate partner validation results and experimental data into specific, actionable technical improvement points for the rest of the team, and follow their incorporation through successive design cycles. - Align targets across internal teams. Partner closely with internal dataset, computational chemistry, machine-learning, and generative-modeling teams to keep property targets, screening oracles, and reward objectives aligned with partner-defined qualification criteria. ESSENTIAL SKILLS & EXPERIENCE - PhD in Chemistry, Chemical Engineering, Materials Science, or a related field, with deep specialization in semiconductor process materials and/or fluorochemistry. - 6+ years of post-PhD experience (or equivalent) in industrial or applied R&D developing, formulating, or qualifying semiconductor process chemicals — including direct, hands-on experience discovering or evaluating PFAS-lean/PFAS-free alternatives for semiconductor manufacturing and adjacent materials (e.g., wet-etch/clean chemistries, lithography materials, heat-transfer fluids, or data-centre/immersion cooling fluids). - Working knowledge of semiconductor unit processes (e.g. lithography, etch, CMP, cleaning, thermal management) and the performance and EHS specifications that govern process-material qualification. - Demonstrated ability to lead application-driven engagements with external industrial partners and to translate fluently between experimental results and computational/modeling requirements. - Proficiency in Python — sufficient to run and configure computational discovery workflows and interpret their outputs — and comfort collaborating with generative-ML and physics-based simulation teams. - Familiarity with generative molecular design, high-throughput virtual screening, or ML property prediction for molecules and materials. HIGHLY DESIRED SKILLS & EXPERIENCE - Direct, hands-on experience with PFAS phase-out or fluorine-free reformulation in a fab or specialty-chemicals setting. - Experience defining qualification protocols or reliability criteria jointly with fabs, OEMs, or chemical suppliers - Track record of publications or patents in semiconductor materials, fluorochemistry, or PFAS alternatives. - Experience operating within a CHIPS Act or other federally funded R&D program. WHY JOIN US? We offer competitive compensation, a comprehensive benefits package, and opportunities for professional growth. - Compensation: Competitive base salary commensurate with experience, plus equity and performance-based incentives. - Benefits: Comprehensive health, dental, and vision insurance; 401(k) with company match; generous parental leave. - Work-Life Balance: Flexible hybrid work arrangements, generous PTO, and a culture that respects focus time and recovery. - Career Development: Direct exposure to CHIPS Act-funded programs, senior scientific and executive leadership, mentorship, and dedicated learning budgets to support continued growth. SANDBOXAQ WELCOMES ALL We are committed to fostering a culture of belonging and respect, where diverse perspectives are actively sought and valued. Our multidisciplinary environment provides ample opportunity for continuous growth - working alongside humble, empowered, and ambitious colleagues ready to tackle epic challenges. Equal Employment Opportunity: All qualified applicants will receive consideration regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. Accommodations: We provide reasonable accommodations for individuals with disabilities in job application procedures for open roles. If you need such an accommodation, please let a member of our Recruiting team know. Read: Guidance for candidates on using AI Tools in interviews https://www.sandboxaq.com/ai-in-interviews

ABOUT SANDBOXAQ SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact. THE OPPORTUNITY SandboxAQ's AI Generation Engine (SAIGE) team is seeking a highly accomplished Machine Learning Engineer to take ownership of the end-to-end ML lifecycle, from initial data exploration and model development to scalable production deployment. This role is central to designing and rapidly building AI-first products that incorporate Large Quantitative Models (LQMs) and sophisticated agentic frameworks. We are looking for a hands-on engineer who is passionate about owning the entire lifecycle of model development. This requires significant industry experience in bringing machine learning models from conception and experimentation to production and deployment in a robust, scalable manner, including (but not limited to): Data Acquisition and Curation, Infrastructure, Pre-Training, Evaluations, and Fine-Tuning. This person will be one of the founding engineers to join the SAIGE team and will be the bridge between cutting-edge AI concepts and functional, real-world MVPs. As a Machine Learning Engineer on the SAIGE team, your primary goal will be to rapidly iterate on different potential solutions to build and evaluate new models, focusing on speed and tangible outcomes. You'll be part of a diverse team consisting of software engineers, ML experts, products managers and user experience researchers, where they will play a key role in efficient and effective enablement of the cutting-edge technologies being developed at SandboxAQ. KEY RESPONSIBILITIES - Design, construct, and manage robust data pipelines for the training, validation, and continuous retraining of Large Quantitative Models (LQMs) and agentic frameworks. - Develop, implement, and rigorously test novel ML models and algorithms, defining appropriate metrics to ensure model performance aligns with high-level product objectives. - Contribute to the efforts in cleaning, transforming, and engineering features from complex and large-scale datasets to optimize LQM performance and predictive accuracy. - Conduct deep analysis of model behavior, performance, and failure modes, tuning hyper-parameters and optimizing model architecture for efficiency, speed, and accuracy in a production context. - Collaborate closely with AI researchers, product managers, and SWEs to translate high-level business objectives into actionable ML development and deployment roadmaps. - Champion and enforce exceptional engineering standards for code quality, system efficiency, and security in a prototyping environment. ESSENTIAL SKILLS & EXPERIENCE - BS in Software Engineering, Computer Science, or equivalent field of study - 5+ years of postgraduate experience in software development - Experience developing highly-available, performant, scalable ML systems, including large-scale data processing pipelines. - Strong expertise in Python (including the ML stack: PyTorch, TensorFlow, JAX, NumPy, Pandas) - Long, successful history of driving the full ML lifecycle: from initial data exploration and hypothe

ABOUT SANDBOXAQ SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact. THE OPPORTUNITY The AI Sim R&D team creates leading edge ML and physics-based models ("LQMs") to advance drug and materials discovery. We are a flexible, creative, and impact driven team of multidisciplinary scientists and engineers, whose products dramatically accelerate the creation of molecules and medicines. As a ML Research Engineer, you will bring cutting edge research into production-grade reality, tasked with making in silico design the dominant paradigm in drug discovery. Your central purpose is to architect, scale, and optimize the scientific codebases that power our LQMs. Over your first year, you will drive the transition of high-impact prototypes into robust products, orchestrate distributed training pipelines on world-class GPU infrastructure, and pioneer hardware-level optimizations that push the boundaries of computational chemistry. KEY RESPONSIBILITIES - Research, Architect, and Scale: Bring novel ideas and the content of scientific papers into high-performing and robust scientific code. - ML Engineering: Lead the ideation, benchmarking, and execution of complex datasets and ML models, ensuring seamless integration into our large-scale simulation frameworks. - Ownership of the Lifecycle: Drive software through the entire product lifecycle—from foundational research and implementation to launch and long-term support—ensuring technical excellence at every stage. ESSENTIAL SKILLS & EXPERIENCE - Academic Foundation: PhD, or research-focused MSc, in Computer Science, Physics, Chemistry, or a related quantitative field focused on advanced computational methods. - Software Excellence: Staff (5+ years) industry experience developing productionized software in professional teams. - Structural Biology Exposure: Experience or training in data-science related tasks related to structural biology. - Research Translation: Expertise translating research papers into concrete ML software artifacts. - Product Lifecycle Mastery: Experience supporting models in external-facing products, demonstrating the ability to bridge the gap between "research code" and "product code". HIGHLY DESIRED SKILLS & EXPERIENCE - Domain Expertise: Direct experience in biopharma or training leading-edge affinity, structure-prediction, or generative chemistry models. - Commercial Insight: A history of developing and launching successful commercial software products within a professional engineering team. - Advanced MLOps: Familiarity with MLOps practices on major cloud platforms to support automated scaling and model monitoring. - Collaborative Innovation: Experience working in interdisciplinary environments where AI intersects with physical or biological sciences. WHY JOIN US? We offer competitive compensation, a comprehensive benefits package, and opportunities for professional growth. - Compensation: Competitive base salary, performance-based incentives or bonuses (where applicable), and equity participation. - Benefits: Comprehensive medical, dental, and

ABOUT SANDBOXAQ SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact. THE OPPORTUNITY SandboxAQ's AI Simulation (AISim) division develops and applies Large Quantitative Models (LQMs) grounded in physics, chemistry, mathematics, and biology to simulate molecular behavior with scientific precision and accelerate discovery across biopharma, chemicals, advanced materials, and more. The Marketing team embedded within AISim is building the commercial engine to bring these capabilities to market — translating frontier science into clear, compelling stories that drive pipeline and customer engagement. The AISim Marketing team is looking for a Product & Growth Marketer to join our team. This role is central to our efforts to fill a critical gap in product marketing and demand generation, from launch planning and outbound campaigns to case studies, thought leadership, and sales enablement. This is a hands-on role for a builder who can move fluidly between positioning and execution, helping shape messaging, create campaign assets, support product launches, and connect SandboxAQ's AI Simulation offerings to the needs of technical and commercial buyers. This person will: - Own end-to-end product marketing and demand generation execution for the AISim business unit, with minimal oversight - Build the positioning, assets, and programs that establish SandboxAQ as a credible and compelling player in the AI simulation market - Partner closely with product, science, and commercial teams to translate complex technical capabilities into buyer-facing value - Grow into a key commercial function as the AISim business scales KEY RESPONSIBILITIES - Develop and refine product positioning and messaging by persona for AI Simulation offerings, translating technical capabilities into buyer-facing value and maintaining consistency across all go-to-market channels - Create campaign and content assets across the funnel (including outbound emails, webinar copy, launch materials, one-pagers, sales sheets, blog content, and website messaging) to drive awareness and pipeline - Lead product and feature launch planning, including narrative development, proof points, and cross-functional coordination with product, growth, and business development teams - Write and maintain sales enablement materials such as collateral, talking points, battlecards, and objection-handling resources that equip the commercial team to engage buyers effectively - Drive demand generation efforts through outbound email programs, webinars, and nurture content, while contributing to customer proof through case studies, white papers, and thought leadership assets ESSENTIAL SKILLS & EXPERIENCE - 4–8 years of experience across product marketing, growth marketing, demand generation, or content marketing in a B2B technology company - Strong writing skills across multiple formats including outbound email, webinar copy, sales collateral, and product launch content - Demonstrated ability to translate technical or scientific concepts into clear, compelling messaging for externa

ABOUT SANDBOXAQ SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact. THE OPPORTUNITY The AI Generation Engine (SAIGE) team is responsible for rapidly designing, prototyping, and validating AI-first SaaS products that leverage SandboxAQ’s Large Quantitative Models (LQMs) and emerging agentic frameworks. The team operates at high velocity, bridging cutting-edge AI research and production-grade software to unlock new use cases across the company. SandboxAQ's AI Generation Engine (SAIGE) team is seeking a highly accomplished Machine Learning Engineer to take ownership of the end-to-end ML lifecycle, from initial data exploration and model development to scalable production deployment. This role is central to designing and rapidly building AI-first products that incorporate Large Quantitative Models (LQMs) and sophisticated agentic frameworks. We are looking for a hands-on engineer who is passionate about owning the entire lifecycle of model development. This requires significant industry experience in bringing machine learning models from conception and experimentation to production and deployment in a robust, scalable manner, including (but not limited to): Data Acquisition and Curation, Infrastructure, Pre-Training, Evaluations, and Fine-Tuning. This person will be one of the founding engineers to join the SAIGE team and will be the bridge between cutting-edge AI concepts and functional, real-world MVPs. As a Machine Learning Engineer on the SAIGE team, your primary goal will be to rapidly iterate on different potential solutions to build and evaluate new models, focusing on speed and tangible outcomes. You'll be part of a diverse team consisting of software engineers, ML experts, products managers and user experience researchers, where they will play a key role in efficient and effective enablement of the cutting-edge technologies being developed at SandboxAQ. KEY RESPONSIBILITIES - Design, construct, and manage robust data pipelines for the training, validation, and continuous retraining of Large Quantitative Models (LQMs) and agentic frameworks. - Develop, implement, and rigorously test novel ML models and algorithms, defining appropriate metrics to ensure model performance aligns with high-level product objectives. - Lead the effort in cleaning, transforming, and engineering features from complex and large-scale datasets to optimize LQM performance and predictive accuracy. - Conduct deep analysis of model behavior, performance, and failure modes, tuning hyper-parameters and optimizing model architecture for efficiency, speed, and accuracy in a production context. - Collaborate closely with AI researchers, product managers, and SWEs to translate high-level business objectives into actionable ML development and deployment roadmaps. - Champion and enforce exceptional engineering standards for code quality, system efficiency, and security in a prototyping environment - Drive technical execution with high autonomy, making critical design and implementation decisions independently ESSENTIAL SKILLS & EXPER

ABOUT SANDBOXAQ SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact. ABOUT THE TEAM The SandboxAQ AI Generation Engine (SAIGE) team’s mission is to accelerate SandboxAQ’s mission of “Deep Impact at Scale” with a focus on quantitative AI and rapid innovation. More specifically, the SAIGE team aims to: - Build next-generation AI capabilities that establish SandboxAQ as the global pacesetter in quantitative AI. - Identify, incubate, prototype, and launch new AI products for high-potential and longer-term use cases, proving (or disproving) their viability as high-impact, highly profitable business lines. The SAIGE team operates on the following principles: Prototype with Velocity, Explore Boldly, Fail Smart, Learn Fast, Look Forward, and Share Knowledge. Our top priority use case for 2026 is leveraging AI and LQMs to solve some of the most impactful problems in the Finance and Insurance industries. THE OPPORTUNITY As the Director of Product Management for the AI Generation Engine (SAIGE), you will be the PM lead for the team and a key partner to engineering, research, and user research. You will: - Own the product strategy and execution for our efforts in Finance & Risk Modeling, partnering closely with financial services and insurance customers to understand their workflows, risk models, and decision-making processes. - Lead rapid prototyping and innovation across a broad range of new ideas and domains, driving 0→1 product discovery, experimentation, and incubation of high-potential use cases. - Operate in a highly ambiguous, fast-changing environment, providing clarity on priorities, making pragmatic trade-offs, and ensuring we ship impactful prototypes and products. This role is ideal for a seasoned product leader who is energized by uncertainty, enjoys working across disciplines (UXR, engineering, research, business), and is excited to build new AI and quantitative products from the ground up. KEY RESPONSIBILITIES LEAD PRODUCT STRATEGY IN FINANCE & RISK MODELING - Own the product vision, roadmap, and execution for our Finance/Risk portfolio, with a focus on financial services and insurance (e.g., portfolio risk, capital modeling, risk analytics, underwriting, and related workflows). - Develop a deep understanding of customer contexts, including current tools, models, and data flows (e.g., portfolio / risk modeling systems, vendor platforms, internal analytics stacks). - Partner with quantitative researchers, ML engineers, and domain experts to translate customer problems into clear product requirements and model/data needs. - Define success metrics and validation strategies to compare our approaches against existing PML/ERM and portfolio views, and to demonstrate differentiated value. DRIVE RAPID PROTOTYPING AND 0→1 INNOVATION - Identify, evaluate, and prioritize new AI / LQM use cases across multiple domains (beyond Finance/Risk), from early signals to clearer opportunities. - Lead 0→1 product discovery: problem framing, hypothesis development, lightweight customer validation, and rapid iteration on

ABOUT SANDBOXAQ SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact. THE OPPORTUNITY Our team is seeking a Software Engineer to contribute to the development of computational chemistry tools, and bridge the gap from R&D prototypes to stable, well-test, production-ready implementations. As we continue to expand our portfolio of capabilities – spanning physics-based simulations, large-scale data and knowledge graphs, machine learning, and massively parallel computing – we require reliable and efficient software to drive it. We are looking for an experienced engineer who can enhance our team’s work through the creation of clean software and collaboration with a team of computational chemists, physicists, AI experts, and software engineers. This should be founded in a good understanding of the technical challenges and scientific concepts in the drug discovery space, and deep experience building efficient and maintainable implementations of AI- and physics-based simulation software. KEY RESPONSIBILITIES: - Maintain and extend existing scientific software packages, and drive the full lifecycle of new ones: - Architect and implement cutting-edge scientific and ML software alongside subject matter experts - Adopt current practices and ensure stability through testing - Work closely with the Engineering Team to deploy these modules into the SandboxAQ’s simulation platform: - Manage dependencies, containerize, and integrate software into CI/CD pipelines - Integrate with the compute and data backends - Define API endpoints and schemas - Collaborate with the engineering team to build UI components - Maintain and support production deployments of scientific software packages - Foster a work culture of curiosity and kindness ESSENTIAL SKILLS & EXPERIENCES: - Bachelor's degree in a relevant scientific discipline (for example physics, chemistry, biology, or computer science) - At least 5 years professional experience in software development, designing and developing well-maintained software systems and collaborating with domain experts to design solutions that meet their needs - Strong Python proficiency including experience with numeric and performance libraries like Numpy - Experience with ML libraries like PyTorch - Experience with relevant development tools and environments (git, Unix/Linux, cloud-based platforms, containerization) - Experience using LLM tools and coding harnessed to build quickly while producing understandable, secure, maintainable code that’s a strong foundation for long-term development. - Ability to rapidly write good quality code while not letting the perfect become the enemy of the good - Ability to devise, communicate internally and own technical roadmaps, in a self-directed environment - Desire to work in a fast-paced team with diverse professional experiences and viewpoints HIGHLY DESIRED SKILLS & EXPERIENCE: - Experience developing software for scientific applications - Familiarity with open source scientific and molecular libraries such as OpenMM, RDKit, Scikit-learn - Experience with

ABOUT SANDBOXAQ SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact. THE OPPORTUNITY The AI Sim R&D team creates leading edge ML and physics-based models ("LQMs") to advance drug and materials discovery. We are a flexible, creative, and impact driven team of multidisciplinary scientists and engineers, whose products dramatically accelerate the creation of molecules and medicines. As a Research Scientist focusing on Co-Folding & Affinity, you will contribute to building SandboxAQ's next generation of structure prediction and binding affinity models. Working alongside a high-performing team of scientists and engineers, you will help advance the state-of-the-art in protein-ligand co-folding, translating cutting-edge research into scalable workflows that power our drug discovery software. This is an opportunity to do frontier science with real-world impact — developing models that redefine what's possible in computational drug discovery. KEY RESPONSIBILITIES - Develop and Iterate on Co-Folding Models: Implement, experiment with, and refine deep learning models for protein-ligand co-folding and structure prediction, building on the latest research from the field. - Drive Rigorous Benchmarking: Design and execute systematic evaluation pipelines to measure model performance against state-of-the-art methods and internal benchmarks. - Contribute to Research-to-Product Pipelines: Collaborate with senior scientists and engineers to integrate validated models into production-ready drug discovery workflows. - Apply Data-Driven Methods: Employ computational and data analysis techniques to generate insights from structural and sequence datasets, informing model development decisions. - Communicate Findings: Present research progress through internal scientific talks, technical write-ups, and contributions to peer-reviewed publications. - Collaborate Across Teams: Work closely with multidisciplinary teams — including ML engineers, structural biologists, and software engineers — to prototype and scale impactful solutions. ESSENTIAL SKILLS & EXPERIENCE - Domain Foundation: Ph.D. in Computational Biology, Biophysics, Computer Science, Computational Chemistry, or a related field, with a research focus on protein structure prediction, co-folding, or closely related areas. - Hands-On Co-Folding Experience: Direct experience with protein structure prediction or protein-ligand co-folding methods (e.g., AlphaFold2/3, RoseTTAFold, Chai-1, Boltz, or comparable systems), developed through graduate or postdoctoral research. - ML Model Development: Experience developing, training, and validating deep learning models, including familiarity with architectures relevant to structural biology (e.g., transformers, equivariant neural networks, diffusion models). - Programming Proficiency: Strong proficiency in Python and modern ML frameworks (PyTorch and/or JAX). - Scientific Rigor: Demonstrated ability to design controlled experiments, interpret results critically, and iterate effectively on model development. - Communication and Collab

ABOUT SANDBOXAQ SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact. THE OPPORTUNITY The AI Sim R&D team creates leading edge ML and physics-based models ("LQMs") to advance drug and materials discovery. We are a flexible, creative, and impact driven team of multidisciplinary scientists and engineers, whose products dramatically accelerate the creation of molecules and medicines. As a Staff ML Research Scientist focusing on Co-Folding & Affinity, you will occupy a senior position architecting our ML biopharma capabilities. Your central purpose is to redefine the state-of-the-art in structure prediction and binding affinity, transforming these breakthroughs into core components of our software suite. Within your first year, you will: pioneer novel deep learning architectures that surpass current benchmarks, orchestrate the seamless integration of these models into production-ready drug discovery pipelines, and solidify SandboxAQ’s scientific authority through high-impact publications and industry-shaping research. KEY RESPONSIBILITIES - Pioneer Novel Architectures: Drive the research and development of next-generation deep learning models for protein-ligand co-folding and affinity prediction. - Architect Product Integration: Bridge from research to commercial utility by equipping SandboxAQ’s software products with advanced predictive capabilities. - Orchestrate Technical Strategy: Bring novel ideas and the content of scientific papers into the ideation, training, and benchmarking of complex models, ensuring they are optimized for large-scale, real-world drug discovery applications. - Champion Scientific Excellence: Act as a technical beacon for the team, representing SandboxAQ scientifically and shaping its vision externally and internally. - Scale High-Performing Teams: Mentor junior researchers and collaborate across engineering and product teams to foster a culture of technical rigor and rapid iteration. ESSENTIAL SKILLS & EXPERIENCE - World-Class Domain Expertise: PhD in Computer Science, Computational Chemistry, or a related field, with specific focus on structure-based deep learned affinity modelling a plus. - Proven Industrial Impact: At least 4 years of post-PhD experience, including experience in a professional industry setting, with a track record of delivering scientific impact that translates to product. - Frontier Technical Skills: Direct, hands-on experience developing and executing leading-edge co-folding and/or affinity prediction models, from proof of concept to productionized workflows. - Domain-Specific Excellence: Proven excellence in co-folding and/or affinity prediction, as demonstrated by participation in industrial projects and/or academic publications. - Professional Engineering Fluency: Experience functioning within a professional software team, including proficiency in Python and modern ML frameworks (PyTorch/JAX) at scale. HIGHLY DESIRED SKILLS & EXPERIENCE - Postdoctoral Experience: In deep learned structure-based affinity models. - Commercial Success: Experience shipping c

ABOUT SANDBOXAQ SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact. ABOUT THE TEAM The SandboxAQ AI Generation Engine (SAIGE) team’s mission is to accelerate SandboxAQ’s mission of “Deep Impact at Scale” with a focus on quantitative AI and rapid innovation. More specifically, the SAIGE team aims to: - Build next-generation AI capabilities that establish SandboxAQ as the global pacesetter in quantitative AI. - Identify, incubate, prototype, and launch new AI products for high-potential and longer-term use cases, proving (or disproving) their viability as high-impact, highly profitable business lines. The SAIGE team operates on the following principles: Prototype with Velocity, Explore Boldly, Fail Smart, Learn Fast, Look Forward, and Share Knowledge. Our top priority use case for 2026 is leveraging AI and LQMs to solve some of the most impactful problems in the Finance and Insurance industries. THE OPPORTUNITY As the Director of Product Management for the AI Generation Engine (SAIGE), you will be the PM lead for the team and a key partner to engineering, research, and user research. You will: - Own the product strategy and execution for our efforts in Finance & Risk Modeling, partnering closely with financial services and insurance customers to understand their workflows, risk models, and decision-making processes. - Lead rapid prototyping and innovation across a broad range of new ideas and domains, driving 0→1 product discovery, experimentation, and incubation of high-potential use cases. - Operate in a highly ambiguous, fast-changing environment, providing clarity on priorities, making pragmatic trade-offs, and ensuring we ship impactful prototypes and products. This role is ideal for a seasoned product leader who is energized by uncertainty, enjoys working across disciplines (UXR, engineering, research, business), and is excited to build new AI and quantitative products from the ground up. KEY RESPONSIBILITIES LEAD PRODUCT STRATEGY IN FINANCE & RISK MODELING - Own the product vision, roadmap, and execution for our Finance/Risk portfolio, with a focus on financial services and insurance (e.g., portfolio risk, capital modeling, risk analytics, underwriting, and related workflows). - Develop a deep understanding of customer contexts, including current tools, models, and data flows (e.g., portfolio / risk modeling systems, vendor platforms, internal analytics stacks). - Partner with quantitative researchers, ML engineers, and domain experts to translate customer problems into clear product requirements and model/data needs. - Define success metrics and validation strategies to compare our approaches against existing PML/ERM and portfolio views, and to demonstrate differentiated value. DRIVE RAPID PROTOTYPING AND 0→1 INNOVATION - Identify, evaluate, and prioritize new AI / LQM use cases across multiple domains (beyond Finance/Risk), from early signals to clearer opportunities. - Lead 0→1 product discovery: problem framing, hypothesis development, lightweight customer validation, and rapid iteration on

ABOUT SANDBOXAQ SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact. THE OPPORTUNITY SandboxAQ's AI Generation Engine (SAIGE) team is seeking a highly accomplished Machine Learning Engineer to take ownership of the end-to-end ML lifecycle, from initial data exploration and model development to scalable production deployment. This role is central to designing and rapidly building AI-first products that incorporate Large Quantitative Models (LQMs) and sophisticated agentic frameworks. We are looking for a hands-on engineer who is passionate about owning the entire lifecycle of model development. This requires significant industry experience in bringing machine learning models from conception and experimentation to production and deployment in a robust, scalable manner, including (but not limited to): Data Acquisition and Curation, Infrastructure, Pre-Training, Evaluations, and Fine-Tuning. This person will be one of the founding engineers to join the SAIGE team and will be the bridge between cutting-edge AI concepts and functional, real-world MVPs. As a Machine Learning Engineer on the SAIGE team, your primary goal will be to rapidly iterate on different potential solutions to build and evaluate new models, focusing on speed and tangible outcomes. You'll be part of a diverse team consisting of software engineers, ML experts, products managers and user experience researchers, where they will play a key role in efficient and effective enablement of the cutting-edge technologies being developed at SandboxAQ. KEY RESPONSIBILITIES - Design, construct, and manage robust data pipelines for the training, validation, and continuous retraining of Large Quantitative Models (LQMs) and agentic frameworks. - Develop, implement, and rigorously test novel ML models and algorithms, defining appropriate metrics to ensure model performance aligns with high-level product objectives. - Contribute to the efforts in cleaning, transforming, and engineering features from complex and large-scale datasets to optimize LQM performance and predictive accuracy. - Conduct deep analysis of model behavior, performance, and failure modes, tuning hyper-parameters and optimizing model architecture for efficiency, speed, and accuracy in a production context. - Collaborate closely with AI researchers, product managers, and SWEs to translate high-level business objectives into actionable ML development and deployment roadmaps. - Champion and enforce exceptional engineering standards for code quality, system efficiency, and security in a prototyping environment. ESSENTIAL SKILLS & EXPERIENCE - BS in Software Engineering, Computer Science, or equivalent field of study - 5+ years of postgraduate experience in software development - Experience developing highly-available, performant, scalable ML systems, including large-scale data processing pipelines. - Strong expertise in Python (including the ML stack: PyTorch, TensorFlow, JAX, NumPy, Pandas) - Long, successful history of driving the full ML lifecycle: from initial data exploration and hypothe

ABOUT SANDBOXAQ SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact. THE OPPORTUNITY SandboxAQ's AI Simulation (AISim) division develops and applies Large Quantitative Models (LQMs) grounded in physics, chemistry, mathematics, and biology to simulate molecular behavior with scientific precision and accelerate discovery across biopharma, chemicals, advanced materials, and more. The Marketing team embedded within AISim is building the commercial engine to bring these capabilities to market — translating frontier science into clear, compelling stories that drive pipeline and customer engagement. The AISim Marketing team is looking for a Product & Growth Marketer to join our team. This role is central to our efforts to fill a critical gap in product marketing and demand generation, from launch planning and outbound campaigns to case studies, thought leadership, and sales enablement. This is a hands-on role for a builder who can move fluidly between positioning and execution, helping shape messaging, create campaign assets, support product launches, and connect SandboxAQ's AI Simulation offerings to the needs of technical and commercial buyers. This person will: - Own end-to-end product marketing and demand generation execution for the AISim business unit, with minimal oversight - Build the positioning, assets, and programs that establish SandboxAQ as a credible and compelling player in the AI simulation market - Partner closely with product, science, and commercial teams to translate complex technical capabilities into buyer-facing value - Grow into a key commercial function as the AISim business scales KEY RESPONSIBILITIES - Develop and refine product positioning and messaging by persona for AI Simulation offerings, translating technical capabilities into buyer-facing value and maintaining consistency across all go-to-market channels - Create campaign and content assets across the funnel (including outbound emails, webinar copy, launch materials, one-pagers, sales sheets, blog content, and website messaging) to drive awareness and pipeline - Lead product and feature launch planning, including narrative development, proof points, and cross-functional coordination with product, growth, and business development teams - Write and maintain sales enablement materials such as collateral, talking points, battlecards, and objection-handling resources that equip the commercial team to engage buyers effectively - Drive demand generation efforts through outbound email programs, webinars, and nurture content, while contributing to customer proof through case studies, white papers, and thought leadership assets ESSENTIAL SKILLS & EXPERIENCE - 4–8 years of experience across product marketing, growth marketing, demand generation, or content marketing in a B2B technology company - Strong writing skills across multiple formats including outbound email, webinar copy, sales collateral, and product launch content - Demonstrated ability to translate technical or scientific concepts into clear, compelling messaging for externa

ABOUT SANDBOXAQ SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact. THE OPPORTUNITY The AI Generation Engine (SAIGE) team is responsible for rapidly designing, prototyping, and validating AI-first SaaS products that leverage SandboxAQ’s Large Quantitative Models (LQMs) and emerging agentic frameworks. The team operates at high velocity, bridging cutting-edge AI research and production-grade software to unlock new use cases across the company. SandboxAQ's AI Generation Engine (SAIGE) team is seeking a highly accomplished Machine Learning Engineer to take ownership of the end-to-end ML lifecycle, from initial data exploration and model development to scalable production deployment. This role is central to designing and rapidly building AI-first products that incorporate Large Quantitative Models (LQMs) and sophisticated agentic frameworks. We are looking for a hands-on engineer who is passionate about owning the entire lifecycle of model development. This requires significant industry experience in bringing machine learning models from conception and experimentation to production and deployment in a robust, scalable manner, including (but not limited to): Data Acquisition and Curation, Infrastructure, Pre-Training, Evaluations, and Fine-Tuning. This person will be one of the founding engineers to join the SAIGE team and will be the bridge between cutting-edge AI concepts and functional, real-world MVPs. As a Machine Learning Engineer on the SAIGE team, your primary goal will be to rapidly iterate on different potential solutions to build and evaluate new models, focusing on speed and tangible outcomes. You'll be part of a diverse team consisting of software engineers, ML experts, products managers and user experience researchers, where they will play a key role in efficient and effective enablement of the cutting-edge technologies being developed at SandboxAQ. KEY RESPONSIBILITIES - Design, construct, and manage robust data pipelines for the training, validation, and continuous retraining of Large Quantitative Models (LQMs) and agentic frameworks. - Develop, implement, and rigorously test novel ML models and algorithms, defining appropriate metrics to ensure model performance aligns with high-level product objectives. - Lead the effort in cleaning, transforming, and engineering features from complex and large-scale datasets to optimize LQM performance and predictive accuracy. - Conduct deep analysis of model behavior, performance, and failure modes, tuning hyper-parameters and optimizing model architecture for efficiency, speed, and accuracy in a production context. - Collaborate closely with AI researchers, product managers, and SWEs to translate high-level business objectives into actionable ML development and deployment roadmaps. - Champion and enforce exceptional engineering standards for code quality, system efficiency, and security in a prototyping environment - Drive technical execution with high autonomy, making critical design and implementation decisions independently ESSENTIAL SKILLS & EXPER

ABOUT SANDBOXAQ SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact. THE OPPORTUNITY We are seeking a VP of Operations to serve as the operational architect for our AI Simulation business unit at SandboxAQ. This is a role for a Builder-Operator to drive rigorous processes and deliver transformative impact by scaling operational infrastructure, developing innovative capacity planning, and navigating complex data-oriented processes all through high EQ influential team leadership. In this role, you will be the operational engine propelling two of our most ambitious divisions centralized under AI Simulation: BioSim (Drug Discovery) and ChemSim (Materials Science). This is a role for a specialist in scaled execution. The ideal candidate is deeply tactical and data-oriented and possesses the high EQ necessary to navigate complex people dynamics. When you aren't developing dashboards to unblock the team, you are performing root-cause analysis on why a process or a team is getting stuck, and using influence to guide change, and ensure both units are positioned for global scale. You will build and spearhead a division that is defining the future of AI-driven science. You will have the purview of a COO with the backing of a world-class organization, focused on solving the world's hardest problems in chemistry and biology. KEY RESPONSIBILITIES Strategic Business Architect: Provide operational support and leadership to BioSim and ChemSim divisions, running day-to-day business operations including identifying synergies in resource allocation and operationalizing scaling systems. As a key leader on a growing team your impact will come from your ability to influence and partner with Engineering, Science, and GTM. Rigorous Resourcing & Capacity Management: Lead the transition from high-growth experimentation to scaled operations by optimizing talent density and capacity across PhDs, SWEs, and GTM specialists. You will architect dynamic headcount models that align hiring with technical milestones and vertical-specific revenue triggers while being accountable for multi-million dollar compute budgets. You will introduce and manage telemetry around human resource capacity allocation across AI Simulation. Tactical Execution: Be responsible for hands-on and end to end execution, track velocity across complex milestones, and rapidly shift resources (financial and talent) as requirements arise and shift. You will establish standards for tracking milestones, manage tradeoffs in resource allocation, and communicate effectively across leadership. Interim Leadership & Chemical Simulation Oversight: Spearhead the Chemical Simulation business unit during its expansion. Your central mandate is to swiftly establish and operationalize high-priority verticals, including but not limited to Batteries, Catalysis Discovery, Semiconductor Substrates, Metal Alloys, and Magnets. You will define the playbook for how we resource and scale these initiatives and identify synergies in resource allocation, orchestration of compute requirements, an