Jobs at SandboxAQ

The Staff ML Research Scientist will pioneer deep learning architectures for drug discovery, driving technical strategy and mentoring junior researchers.

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 top-of-funnel talent sourcing for frontier tech roles (AI, quantum, cybersecurity, life sciences). Build advanced market maps, use OSINT and alternative channels to identify passive candidates, manage executive stakeholders, craft high-touch candidate experiences, and drive hiring strategy for highly specialized, low-visibility talent pools.

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 the execution of catalysis validation programs, coordinating among computational scientists, engineers, and external partners to translate results into real-world outcomes. Drive processes and metrics for program management and report on progress to leadership.

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 Director will lead corporate development strategies, manage acquisition processes, and foster strategic partnerships to drive growth at SandboxAQ.

The Manager of Clinical Research leads AQMed's clinical program, overseeing multi-center studies globally, managing external partners, and ensuring regulatory compliance while integrating AI tools to enhance efficiency.

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.

The role involves developing computational chemistry tools, implementing AI and physics-based simulations, and maintaining scientific software systems while collaborating with experts across various fields.

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

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 end-to-end machine learning lifecycle management, including data processing, model development, rigorous testing, and production deployment, focusing on large quantitative models for AI-first products.

The Director of Product Management will lead product strategy for AI solutions in finance, focusing on innovation and collaboration across disciplines while managing customer relationships and rapid prototyping of financial applications.