ML Research Engineer
1 week ago
Genesis AI team is focused on developing foundation models for small molecule 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 experienced ML research engineers to join the team and lead research and engineering efforts focused on driving forward our ML research agenda for generative modeling of molecular systems, which is instrumental to our mission.
As a ML Research Engineer at Genesis, you will drive forward novel ML experimentation, ideation, execution, and analyses of results on the path towards building larger and more powerful generative and predictive models of biomolecular systems of increasing complexity. Blending together techniques from cutting edge machine learning (denoising diffusion, equivariant architectures, self-supervised training of multi-modal models, RL-based alignment) and computational physics/chemistry (molecular dynamics, quantum mechanics), you will lead rapid iteration on our AI platform unlocking the next level of performance, efficiency, and scale that was not previously possible.
Genesis is a highly-collaborative and cross functional environment, and you will work in close partnership with our exceptional engineers, researchers, and biochemistry experts.
Positions are available at various levels of seniority, starting from Senior and above. You will
- Lead experimentation on transformative research projects that enhance the Genesis AI platform's capabilities, focusing on generative and predictive models for molecular systems.
- Carefully design and run experiments at scale to validate most promising approaches, leading ML engineering efforts and shipping state-of-the-art models to production.
- Navigate the latest deep learning literature, extracting insights from generative modeling in adjacent domains (language, images, 3D graphics, etc.), developing novel models and training techniques for molecular data, and communicating your findings to the team.
- 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.
- Independent thinker with a strong sense of ownership and capability of driving research projects or engineering robust systems from first-principles-based conceptualization to state-of-the-art realization.
- Experienced in contributing to challenging deep learning research projects, designing and iterating on novel model architectures, training and inference algorithms, etc.
- Experienced with running, scaling up, and analyzing distributed training experiments.
- 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).
- Strong engineer who constantly strives for technical excellence. You can write clean code and have a deep understanding of the codebases you work in.
- MS or PhD in machine learning, computer science, other computational sciences or equivalent research or engineering experience (3+ years) and publication record at top tier ML venues are preferred.
- 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, or other cutting edge generative or predictive machine learning models.
- 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.
- 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.
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 three AI platform collaborations across a range of therapeutic areas, with Gilead Sciences, Eli Lilly, and Genentech.
We raised a $200M series B in August 2023, and have raised over $300M 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.
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