Genesis Molecular AI · 3 weeks ago
ML Research Engineer, Foundation Models (Senior / Staff / Principal)
Burlingame, CA
Full-time
Hybrid
Senior Level, Lead/Staff
3+ years expGenesis Molecular AI is pioneering foundation models for molecular AI to unlock a new era of drug design and development. They are seeking a highly-skilled ML Research Engineer to drive the R&D and scaling of foundation models while collaborating with multidisciplinary teams to translate cutting-edge concepts into robust models for drug discovery.
Artificial Intelligence (AI)BiotechnologyInformation Technology
Responsibilities
Drive the R&D and scaling of our foundation models, taking ownership of the engineering and experimentation for key research initiatives
Make cutting-edge foundation model research a reality at scale. Implement, optimize, and build novel foundation models from the initial research prototypes to high-performance production models. You will constantly engage with deep learning literature, building upon novel architectures and training methods to create new capabilities
Own the experimental lifecycle with scientific rigor. You'll design experimental plans, own their execution on our large-scale compute infrastructure, and drive the deep analysis of results to inform the next research cycle and to validate most promising approaches
Engineer our models for state-of-the-art performance, optimizing the scalability and efficiency of every part of the training and inference pipeline
Ship state-of-the-art models to production, working closely with the broader team to integrate your models into our drug discovery platform
Collaborate intensely with a multidisciplinary team to forge a tight, fast-moving loop between idea, implementation, and discovery
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 high-quality code, rigorous experimentation, and continuous innovation
Qualification
Required
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 your 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 our culture of intellectual curiosity and the shared belief that breakthroughs happen when diverse perspectives and minds unite
Preferred
A MS or PhD in machine learning, computer science, other computational sciences or equivalent research or engineering experience (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 our core libraries: PyTorch, PyTorch Lightning, and Ray Distributed Training, PyTorch Geometric, etc
Experience with novel research in one or more of the following domains: LLMs, diffusion, reinforcement learning or other cutting edge generative or predictive machine learning models
Familiarity with molecular data (proteins, small molecules), physics-informed ML, or 3D point cloud data
Benefits
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.
Company
Genesis Molecular AI
Genesis Therapeutics unifies AI and biotech to accelerate the discovery of new medicines.
51-200 employees
H1B Sponsorship
Genesis Molecular AI has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (3)
2024 (1)
2023 (1)
2022 (1)
Funding
Current Stage
Growth StageTotal Funding
$256.1MKey Investors
Andreessen HorowitzRock Springs Capital
2023-08-21Series B· $200M
2020-12-02Series A· $52M
2020-04-01Series Unknown
Leadership Team
Evan Feinberg
Founder and CEO
Aleksandra Faust
Chief AI Officer
Recent News
Genetic Engineering News
2025-12-10
MIT Technology Review
2025-11-27
Company data provided by crunchbase