ML Research Scientist (Senior / Staff / Principal)

You will

• Lead transformative research projects from conception to implementation, tackling core challenges in generative modeling for molecular systems.
• Design and develop novel models and algorithms, building upon the latest literature in diffusion models, flow matching, RL, LLMs, and other cutting-edge areas.
• Execute ambitious experiments at scale, leveraging our world-class computational infrastructure to rigorously validate your hypotheses and push the boundaries of the state-of-the-art.
• Collaborate intensely with a multidisciplinary team to translate your research into tangible impact on our drug discovery platform.
• Contribute to the global research community by publishing some of your work and representing Genesis at top tier AI/ML conferences and workshops.
• Mentor and guide other researchers and engineers, fostering a culture of shared learning, growth, and innovation.

You are

• A deep learning expert with a portfolio of novel research in one or more cutting-edge domains of generative or predictive modeling (e.g., diffusion, flow matching, RL, foundation model architectures and training methods).
• An independent, first-principles thinker with a strong sense of ownership over your research projects and a drive to see them through to completion.
• A strong coder, comfortable with going deep into the engineering stack to build, debug, and ship your own models.
• 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 our culture of intellectual curiosity and the shared belief that breakthroughs happen when diverse perspectives and minds unite.

Nice to have's

• PhD in machine learning, computer science, other computational sciences or equivalent research experience, demonstrated by a strong publication record.
• Hands-on experience with Pytorch, Pytorch Lightning, Ray Distributed Training, Pytorch Geometric, etc.
• Experience in distributed training and inference of large models on GPU clusters.
• Familiarity with molecular data, (proteins, small molecules), physics-informed ML, or 3D point cloud data.

Compensation, Benefits, and Perks

• Competitive compensation package that includes salary and equity.
• Comprehensive health benefits: Medical, Dental, and Vision (covered 100% for the 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.