Jobs at SandboxAQ

Join SandboxAQ as a Scientific Software Engineer to develop AI-driven computational chemistry tools and maintain production-quality software, collaborating with experts to enhance drug discovery processes.

The role involves managing the ML lifecycle, developing scalable ML systems, and collaborating on AI-first product solutions focusing on Large Quantitative Models.

Act as the technical lead between LQMs and client contracts: diagnose workflows, design and deploy software and infrastructure, wrap scientific logic, integrate agentic systems, and own end-to-end compute and data pipeline deployments to enable scientific delivery.

The Senior Backend Engineer will develop core functionalities for AI-driven drug discovery, collaborating with R&D and product teams, managing infrastructure, and ensuring engineering excellence.

The Senior Forward Deployed Engineer will deploy and validate AQNav systems, drive success during tests, communicate with stakeholders, and bridge operations with research and engineering.

The Staff ML Research Scientist will lead research in deep learning for drug discovery, develop innovative models, and integrate them into commercial software. Responsibilities include mentoring junior researchers and contributing to scientific publications.

Lead FP&A activities including annual and rolling forecasts, budgeting, variance analysis, program-level financial reporting, and building scalable models and dashboards. Partner with business leaders, operations, GTM, accounting and legal to translate strategy and customer commitments into financial plans, revenue commitments, and program performance metrics while strengthening FP&A controls and automation in a high-growth environment.

Develop and iterate deep learning models for protein-ligand co-folding and structure prediction, benchmark performance, integrate validated models into production drug-discovery pipelines, analyze structural and sequence data, communicate findings, and collaborate with multidisciplinary teams to scale research into products.

The Director of Product Management for AI Generation Engine will lead product strategy and execution in Finance & Risk Modeling, focusing on innovative AI solutions and close collaboration with financial services clients.

Lead microkinetic and reactor-level modeling workflows for catalytic processes, collaborating with industrial partners, and mentoring junior scientists while refining models based on experimental data.

The Data Engineer will develop and maintain data pipelines, build data models, ensure data quality, and support cross-functional teams while improving internal data platform infrastructure and documentation.

Lead product strategy and development for AI Simulation products, translating scientific needs into product requirements and ensuring market fit.

The Staff Technical Product Manager will drive product strategy and definition for AI solutions targeting life sciences, ensuring alignment across teams, validating product market fit, and leading product launch activities.

The VP of Operations will architect the AI Simulation business unit, optimize processes, manage resources, and lead strategic initiatives in AI-driven science, overseeing BioSim and ChemSim divisions.

As a Research Scientist, you will develop large-scale datasets, support computational workflows for catalysis, mentor junior scientists, and engage with industrial partners for catalyst discovery.

Lead the end-to-end machine learning lifecycle for AI products, managing data pipelines and model development to optimize performance and accuracy in production.