🛠 Tech Stack

💼 About This Role

You'll work embedded with ML scientists to co-develop and refine model training and evaluation workflows. You'll translate experimental research code into maintainable, reusable systems and build benchmarking infrastructure for structural and affinity datasets. This role offers hands-on experience at the intersection of drug discovery and machine learning engineering, turning research into scalable tools.

🎯 What You'll Do

• Embed with ML scientists to co-develop training and evaluation workflows.
• Translate experimental research code into maintainable, reusable systems.
• Build and expand benchmarking systems for structural and affinity datasets.
• Develop tooling and interfaces to expose new capabilities to researchers.

📋 Requirements

• 8+ years of software engineering experience
• Strong Python skills with software engineering rigor
• Experience working closely with ML practitioners or in research environments
• Experience building ML workflows, data pipelines, or evaluation systems

✨ Nice to Have

• Experience with scientific or computational research environments
• Familiarity with structural biology, chemistry, or molecular modeling
• Exposure to cloud systems (AWS, Kubernetes) or HPC

🎁 Benefits & Perks

• 💰 Competitive salary and company paid healthcare
• 🏖️ Uncapped vacation
• 🏋️ Onsite gym in San Diego office
• 🏦 401K matching
• 🩺 Flexible spending accounts and voluntary life insurance

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3Team Interview· 60 min
4. 4Offer· 30 min