ML Research Engineer

Employment Type: Full-time

Position Overview

Genesis AI team is focused on developing foundation models for small molecule drug discovery. We conduct fundamental research at the intersection of machine learning, physics, and computational chemistry, and engineer robust software systems. These systems enable large-scale simulations and the training of generative and predictive AI models designed to learn from all kinds of molecular data, leveraging our cluster with thousands of GPUs and tens of thousands of CPUs.

We are a tight-knit team of proven drug hunters, deep learning researchers, and software engineers united by a common mission: to drive AI innovation in biochemistry and discover/develop groundbreaking therapies for patients suffering from severe disorders.

About the Role

We are seeking experienced ML Research Engineers to join our 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 an 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 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.

Responsibilities

• 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 the 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.
• Mentor and guide more junior members of our technical team, as well as research interns, fostering an environment of growth and innovation.

You Are

• An independent thinker with a strong sense of ownership and the capability to drive research projects or engineer 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.
• Experienced with running, scaling up, and analyzing distributed training experiments.
• A curious, problem-oriented thinker 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 is necessary).
• A strong engineer who constantly strives for technical excellence. You can write clean code and have a deep understanding of the codebases you work in.

Nice to Haves

• MS or PhD in machine learning, computer science, other computational sciences, or equivalent research or engineering experience (3+ years) and a publication record at top-tier ML venues are preferred.
• Deep learning expertise 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 models.