ML Research Scientist

3 weeks ago


Burlingame, United States Genesis Therapeutics Full time

About The Team

We’re a tight-knit team of proven drug hunters, deep learning researchers, and software engineers united by a common mission — drive AI innovation in biochemistry, discovering and developing groundbreaking therapies for patients suffering from severe disorders.

The Genesis AI team is focused on developing foundation models for drug discovery by conducting fundamental research at the intersection of machine learning, physics, and computational chemistry, as well as engineering robust software systems that enable running large scale simulations and training generative and predictive AI models designed to learn from all kinds of molecular data, leveraging our cluster with 1000s of GPUs and 10,000s of CPUs.

About The Role

We’re seeking an experienced ML Research Scientist to shape and lead the ML research agenda for generative modeling of molecular systems, which is instrumental to our mission. You will be at the forefront of pioneering research initiatives, driving the continuous evolution and enhancement of our AI platform, while collaborating with exceptional engineers, researchers, and a team of biochemistry experts.

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

You will

  1. Lead transformative research projects that enhance the Genesis AI platform's capabilities, focusing on generative models for molecular systems.
  2. Navigate the latest deep learning literature, extracting insights from generative modeling in adjacent domains (language, images, 3D graphics, etc.), develop novel models and training techniques for molecular data, and communicate your findings to the team.
  3. Carefully design and run experiments at scale to validate the most promising approaches and work closely with engineers to ship state-of-the-art models to production.
  4. Contribute to the research community by publishing some of our findings in the form of research papers and blog posts at top tier AI/ML venues (NeurIPS, ICML, ICLR, etc.), attending conferences and workshops, and engaging in continuous learning and knowledge exchange.
  5. Have the opportunity to mentor and guide more junior members of our technical team as well as research interns, fostering an environment of growth and innovation.

You are

  1. A deep learning expert with a track record of doing novel research in one or more of the following domains: denoising diffusion, normalizing flows, flow matching, neural ODEs and SDEs, or other cutting edge generative or predictive machine learning models.
  2. Independent thinker with a strong sense of ownership and capability of driving research ideas from first-principles-based conceptualization to state-of-the-art realization.
  3. Strong coder who is not afraid of deep dives into engineering whenever necessary.
  4. Curious, problem-oriented thinker who is excited to dive deep into the emerging field at the intersection of AI, physics, chemistry, and biology and make foundational contributions and discoveries (no previous experience in anything but ML necessary).

Nice to haves

  1. PhD in machine learning, computer science, other computational sciences or equivalent research experience and strong publication record at top tier ML venues are preferred.
  2. Hands-on experience with some of the core libraries we use: Pytorch, Pytorch Lightning, Pytorch Geometric.
  3. Experience in distributed training and inference of large models on GPU clusters.
  4. Experience working with some of the following: molecular systems (protein sequences and 3D structures, small molecules, etc.), ML force fields or other physics-informed models and methods, or point cloud data in other application domains, such as 3D graphics.

Compensation, Benefits, And Perks

  1. Competitive compensation package that includes salary and equity.
  2. Comprehensive health benefits: Medical, Dental, and Vision (covered 100% for the employees).
  3. 401(k) plan.
  4. Open (unlimited) PTO policy.
  5. Free lunches and dinners at our offices.
  6. Paid family leave (maternity and paternity).
  7. Life and long- and short-term disability insurance.

About Genesis Therapeutics

Genesis Therapeutics is unifying AI and biotech to discover novel and breakthrough treatments for patients with severe and devastating conditions. Genesis was founded on groundbreaking molecular ML research and since has established itself as the industry leader in AI for small molecule drug discovery. Our team of accomplished biotech leaders and expert drug hunters joins forces with deep learning researchers and software engineers who are pioneering predictive and generative AI technologies for molecules.

Our team has created the industry's most advanced molecular AI platform called GEMS (Genesis Exploration of Molecular Space), to accelerate and optimize small molecule drug discovery and to enable the discovery of novel first-in-class and best-in-class small molecule drugs for challenging and/or undruggable targets.

The company has leveraged GEMS to build an internal pipeline with multiple programs against high-value targets, including data-poor and canonically undruggable targets where GEMS is uniquely advantaged. In addition, Genesis has two AI platform collaborations across a range of therapeutic areas: Eli Lilly (signed in 2022, with a $20M upfront payment and a $670M total deal size), and Genentech (signed in 2020).

We raised a $200M series B in August 2023, and have raised over $280M in funding from top technology and biotech investors, including Andreessen Horowitz, Rock Springs Capital, T. Rowe Price, Fidelity, Radical Ventures, NVentures (NVIDIA's VC arm), BlackRock, and Menlo Ventures.

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

Finding the best talent is our top priority at Genesis Therapeutics. If you are interested in potential partnership on recruitment, please reach out to recruiting@genesistherapeutics.ai.

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