Merge Labs
ML Research Scientist - De Novo Design
$200K–$270K
San Francisco Bay Area · On-site · Full-time · Posted Dec 11, 2025
About the job
Design and scale machine-learning frameworks for de novo molecular design and closed-loop optimization, connecting experimental data to discovery workflows.
What you'll do
- Build data and modeling foundations for de novo design and closed-loop optimization in collaboration with data-engineering and MLOps.
- Partner with wet-lab scientists to define optimization objectives, encode domain-specific priors and constraints, and validate model performance.
- Integrate models with experimental data streams and develop methods for multi-objective or constrained optimization.
What they ask for
- Strong grounding in SSMs, LLMs, SE(3)-equivariance, and Flow-matching.
- Working knowledge of transfer-learning strategies.
- Proficiency in Python, PyTorch, and Jax, with ability to write clean, reproducible production-grade code.
- Experience bridging machine learning and experimental science, including work with sparse, noisy, or high-cost data.
Nice to have
- Familiarity with neuroscience.
Pay
$200K – $270K USD base salary
Tools
SSMs, LLMs, SE(3)-equivariance, Flow-matching, Python, PyTorch, Jax
AI focus
Develop de novo design and closed-loop ML optimization frameworks for biomolecular discovery and neuroengineering.
Model-written summary · the original posting is authoritative