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