🛠 Tech Stack

💼 About This Role

You'll architect, scale, and optimize scientific codebases powering Large Quantitative Models (LQMs) for drug and materials discovery. Your core impact is transitioning high-impact prototypes into robust, production-grade products. You'll pioneer hardware-level optimizations and orchestrate distributed training on world-class GPU infrastructure.

🎯 What You'll Do

• Architect and scale ML algorithms from scientific papers into production code.
• Lead benchmarking and execution of complex datasets and ML models.
• Implement GPU optimizations for distributed cloud environments.
• Own full product lifecycle from research to launch and long-term support.

📋 Requirements

• MSc (PhD preferred) in CS, Physics, Chemistry, or related quantitative field.
• 5+ years industry experience developing productionized software.
• Experience training large-scale ML pipelines on distributed GPUs (PyTorch, TensorFlow).
• Familiarity with agentic coding tools (Claude code, Codex).

✨ Nice to Have

• Direct experience in biopharma or training leading-edge molecular models.
• History of developing and launching commercial software products.
• Experience in interdisciplinary AI and physical/biological sciences environments.

🎁 Benefits & Perks

• 💰 Competitive base salary and equity participation.
• 🏥 Comprehensive medical, dental, vision coverage with generous employer contributions.
• 🏖️ Flexible paid time off and company-wide seasonal breaks.
• 📈 Retirement savings with company matching.
• 👶 Paid parental leave and family-building benefits.