ML Research Engineer, Foundation Models (Senior / Staff / Principal)
Genesis Molecular AI1 year ago
San Mateo, CA, USA or New York, NY, USASenior / Staff+
Responsibilities
- Drive R&D and engineering experimentation for foundation models and key research initiatives.
- Implement, optimize, and ship foundation models from research prototypes through high-performance production systems.
- Optimize distributed training, inference efficiency, GPU workloads, and large-scale ML systems.
- Develop novel modeling approaches based on deep learning research and literature.
- Bridge ML systems with computational chemistry, structural biology, and medicinal chemistry workflows.
- Productionize Pearl and related structure prediction models for internal and partner drug discovery pipelines.
- Design and execute rigorous experiments on large-scale compute infrastructure and analyze results.
- Integrate models into the drug discovery platform and active discovery programs.
- Mentor and guide researchers and engineers.
- Publish research and represent Genesis at AI/ML conferences and workshops.
Requirements
- 2+ years of industry experience building complex ML systems.
- Deep expertise in scalable foundation models, pretraining, post-training methods, and related systems.
- Strong Python, PyTorch, and distributed training experience with the ability to translate research into production systems.
- Experience designing, optimizing, and implementing novel ML modeling approaches.
- Experience training models at scale on large datasets and GPU clusters.
- Hands-on experience writing CUDA kernels or optimizing GPU workloads beyond standard frameworks.
- Hands-on experience with PyTorch, PyTorch Lightning, Ray Distributed Training, and PyTorch Geometric.
- Experience with novel research in LLMs, diffusion, reinforcement learning, or other advanced generative or predictive ML models is preferred.
- Experience with computational chemistry, drug discovery systems, protein-ligand structure prediction, small-molecule modeling, or related workflows is preferred.
- Experience with diffusion or other generative modeling methods applied to scientific or molecular problems is preferred.
- Experience with SFT, RLHF, synthetic data pipelines, or other LLM post-training systems is preferred.
- Experience with Triton kernels, TensorRT, quantization, or large-scale model serving is preferred.
- Publications in NeurIPS, ICML, ICLR, or similar venues are preferred.
- Experience with Genesis ML frameworks or related systems is preferred.
- An MS or PhD in machine learning, computer science, computational science, or equivalent research/engineering experience is preferred.
- No prior biology or chemistry experience is required.
Benefits
- Competitive compensation package including salary and equity.
- Medical, dental, and vision coverage fully paid for employees.
- 401(k) plan.
- Open unlimited PTO policy.
- Free lunches and dinners at company offices.
- Paid maternity and paternity leave.
- Life and long- and short-term disability insurance.
- Genesis is headquartered in San Mateo, California, with a fully integrated laboratory in San Diego.
Categories
AI ResearchML Engineering
About Genesis Molecular AI
Genesis Molecular AI develops GEMS, a generative and predictive molecular AI platform that designs and optimizes small‑molecule drug candidates, including the Pearl diffusion model for structure prediction. The company advances an internal discovery pipeline and partners with pharma on AI‑enabled discovery; recent collaborations include Gilead (2024) and Incyte (2025). It is privately held, headquartered in Burlingame, California, with a fully integrated laboratory in San Diego.