Teams at SandboxAQ

Translate cutting-edge ML and physics research into production-grade scientific code, architect and scale large-scale simulation and training pipelines on GPU infrastructure, optimize hardware-level performance, and support models throughout the product lifecycle to accelerate in silico drug and materials discovery.

Lead execution of high-uncertainty R&D programs by building adaptable roadmaps, anticipating bottlenecks, translating between scientists/product/finance, driving resourcing decisions, and orchestrating last-mile launches for milestones, papers, or product moments in AI-driven drug discovery.

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.