ML Research Engineer, Foundation Models; Senior​/Principal

About The Team

Join a world-class team at the forefront of AI and biochemistry. At Genesis Molecular AI, we’re a tight-knit team of proven deep learning researchers, software engineers, and drug discovery pioneers. Our shared mission is revolutionary: to forge the next generation of AI foundation models that will unlock groundbreaking therapies for patients with severe diseases. We conduct fundamental research at the intersection of machine learning, physics, and computational chemistry, pushing the boundaries of each field.

The Genesis AI team is building an engine for this revolution. You will work side by side with the top multidisciplinary researchers to design and build generative foundation models at scale from the entire spectrum of molecular data, with access to ample compute and large-scale simulations.

This role is for a highly-skilled ML Research Engineer who thrives at the intersection of fundamental research and production-grade engineering. As a core member of our Genesis AI team, you will be the engineering pillar for inventing and shipping our next-generation foundation models. You will partner directly with research scientists to design, build, and scale the systems for our most ambitious projects.

You’ll tackle challenges such as scaling model pretraining, advancing reinforcement learning methods, or optimizing post-training pipelines. Your mission is to translate cutting-edge concepts into powerful and robust models that form the backbone of our drug discovery platform.

Positions are available at various levels of seniority:
Senior, Staff, and Principal.

• An exceptional research engineer with deep expertise in building scalable, high-performance foundation models, pretraining, and posttraining methods, and systems around them.
• A master of the modern ML engineering stack, striving for technical excellence with a passion for writing clean, high-performance, and reusable code (Python, PyTorch, etc.).
• An experienced practitioner of ML at scale, with a strong background in distributed training and data parallelism.
• Thrive in the ambiguity of deep learning research, comfortable designing and iterating on novel model architectures and training algorithms.
• An independent, first-principles thinker for both research and engineering problems, who takes pride in projects and strives to build robust impactful models and systems from first-principles-based conceptualization to state-of-the-art realization.
• A curious, problem-oriented mind, excited to dive into the emerging field at the intersection of AI, physics, chemistry, and biology and make foundational contributions and discoveries. No prior experience in biology or chemistry is necessary – only willingness to learn.
• A true team player with strong communication skills who thrives in highly collaborative, mission-driven environments where science and engineering are deeply intertwined.
• Inspired by a culture of intellectual curiosity and the belief that breakthroughs happen when diverse perspectives unite.

• A MS or PhD in machine learning, computer science, or other computational sciences (3+ years) demonstrated by a track record of building complex ML systems.
• A publication record in top-tier ML venues (NeurIPS, ICML, ICLR, etc.).
• Hands-on experience with core libraries:
  PyTorch, PyTorch Lightning, Ray Distributed Training, PyTorch Geometric, etc.
• Experience with novel research in LLMs, diffusion, reinforcement learning or other cutting-edge generative or predictive ML models.
• Familiarity with molecular data (proteins, small molecules), physics-informed ML, or 3D point cloud data.

• Competitive compensation package that includes salary and equity.
• Comprehensive health benefits:
  Medical, Dental, and Vision (covered 100% for employees).
• 401(k) plan.
• Open (unlimited) PTO policy.
• Free lunches and dinners at our offices.
• Paid family leave (maternity and paternity).
• Life and long- and short-term disability insurance.

Genesis Molecular AI pioneers foundation models for molecular AI to unlock a new era of drug design and development. Our generative and predictive AI platform, GEMS (Genesis Exploration of Molecular Space), integrates AI and physics into industry-leading models to generate and optimize drug molecules, including the breakthrough generative diffusion model Pearl for structure prediction. Genesis has raised over $300 million from leading AI, tech and life science-focused investors, signed multiple AI-focused research collaborations with major pharma partners, and is deploying GEMS to advance an internal therapeutics pipeline for a variety of high-impact targets.

Genesis is headquartered in San Mateo, CA, with a fully integrated laboratory in San Diego. We are proud to be an inclusive workplace and an Equal Opportunity Employer.