[Hiring] Staff ML Research Engineer @SandboxAQ

Role Description

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 Engineer, you will be the bridge between visionary research and 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

• Architect and Scale: Bring content of scientific papers into promising, scalable ML algorithms; and translate these 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.
• GPU Expertise: Implement advanced software and hardware optimizations to maximize the efficiency of ML pipelines across distributed cloud GPU environments.
• 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.

Qualifications

• MSc (PhD preferred) in Computer Science, Physics, Chemistry, or a related quantitative field focused on advanced computational methods.
• Senior (5+ years) industry experience developing productionized software in professional teams.
• Proven experience training and optimizing large-scale ML pipelines on distributed cloud GPUs (e.g. PyTorch, TensorFlow).
• Deep familiarity with agentic coding tools (e.g. Claude code, Codex).
• Experience supporting models in external-facing products, demonstrating the ability to bridge the gap between "research code" and "product code".

Highly Desired Skills & Experience

• Direct experience in biopharma or training leading-edge affinity, structure-prediction, or generative chemistry models.
• A history of developing and launching successful commercial software products within a professional engineering team.
• Familiarity with MLOps practices on major cloud platforms to support automated scaling and model monitoring.
• Experience working in interdisciplinary environments where AI intersects with physical or biological sciences.

Benefits

• Competitive base salary, performance-based incentives or bonuses (where applicable), and equity participation.
• 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.
• Flexible paid time off, company-wide seasonal breaks, and support for flexible work arrangements that enable sustainable performance.
• Opportunities for continuous learning and growth through on-the-job development, cross-functional collaboration, and access to internal learning and development programs.