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Molecular Simulation Jobs in California (NOW HIRING)

LLNL

Machine Learning (ML) Bioengineer

Livermore, CA · On-site

$9.7K/wk

As a member of our multidisciplinary team, you will collaborate with experts in machine learning, molecular simulation, optimization, and bioinformatics, and interface with experimentalists ...

LLNL

Machine Learning (ML) Bioengineer

Livermore, CA · On-site

As a member of our multidisciplinary team, you will collaborate with experts in machine learning, molecular simulation, optimization, and bioinformatics, and interface with experimentalists ...

LLNL

Machine Learning (ML) Bioengineer

Livermore, CA · On-site

As a member of our multidisciplinary team, you will collaborate with experts in machine learning, molecular simulation, optimization, and bioinformatics, and interface with experimentalists ...

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Molecular Simulation information

What is a molecular simulation?

A Molecular Simulation job involves using computational techniques to model and analyze molecular systems at the atomic level. Professionals in this field apply physics-based algorithms and software to study material properties, chemical reactions, and biological processes. They work in industries such as pharmaceuticals, materials science, and energy to optimize product development and research. Strong skills in computational chemistry, physics, and programming are essential for this role.

What are the key skills and qualifications needed to thrive in molecular simulation?

To thrive in Molecular Simulation, you need a solid background in chemistry, physics, or computational science, often at the graduate level, with expertise in molecular modeling and statistical mechanics. Familiarity with industry-standard simulation software (such as GROMACS, AMBER, or CHARMM), programming languages (like Python or C++), and high-performance computing platforms is essential. Strong analytical thinking, attention to detail, and effective communication are valuable soft skills in this role. These competencies are crucial for accurately modeling molecular systems, interpreting results, and collaborating with multidisciplinary teams in research or industry settings.

What are some common challenges faced by professionals in molecular simulation?

Professionals in molecular simulation often encounter challenges such as optimizing computational workloads, troubleshooting simulation errors, and interpreting complex data outputs. Balancing the accuracy of simulations with computational efficiency can also be demanding, especially when working with large biomolecular systems or advanced algorithms. Additionally, staying abreast of rapidly evolving software tools and scientific methodologies requires ongoing learning and adaptation. Being able to collaborate with experimental scientists and clearly communicate results is important for integrating simulation findings into broader research projects.

What are popular job titles related to Molecular Simulation jobs in California?

For Molecular Simulation jobs in California, the most frequently searched job titles are:

What job categories do people searching Molecular Simulation jobs in California look for?

The top searched job categories for Molecular Simulation jobs in California are:

What cities in California are hiring for Molecular Simulation jobs?

Cities in California with the most Molecular Simulation job openings:

Molecular Simulation jobs near you
Infographic showing various Molecular Simulation job openings in California as of August 2026, with employment types broken down into 84% Full Time, 14% Part Time, and 2% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution.

ML Research Scientist, Foundation Models (Senior / Staff / Principal)

Genesis Molecular AI

San Mateo, CA • On-site, Remote

$112K - $142K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 8 days ago

Key responsibilities

  • Lead transformative research projects from conception to implementation in generative modeling for molecular systems.

  • Design and develop novel models and algorithms, including diffusion models, flow matching, reinforcement learning, and foundation model architectures.

  • Execute experiments at scale using computational infrastructure to validate hypotheses and advance the state-of-the-art.

Job description

ML Research Scientist, Foundation Models
About the Team
Join a world-class team at the forefront of AI and biochemistry.
At Genesis Molecular AI, we're a tight-knit team of proven deep learning researchers, software engineers, and drug discovery pioneers. Our shared mission is nothing short of revolutionary: to forge the next generation of AI foundation models that will unlock groundbreaking therapies for patients with severe diseases.
We don't just apply machine learning to biology; we are conducting fundamental research at the intersection of machine learning, physics, and computational chemistry, pushing the boundaries of each field. The Genesis AI team is building an engine for this revolution. You will work side by side with the top multidisciplinary researchers to design and build generative and discriminative foundation models at scale from the entire spectrum of molecular data, having access to ample compute and large-scale simulations.
About the Role
This is an opportunity for a scientific innovator to advance the future of generative AI in drug discovery. As a key member of the Genesis AI team, you will shape and drive our research agenda for foundation models. You will lead critical research initiatives in areas like reinforcement learning, novel model architectures, and advanced pretraining and post-training methods. Your core mission is to create groundbreaking models and insights that are instrumental in discovering new medicines.
This role requires a deep curiosity and a collaborative spirit. You will be a strong team player, working in close partnership with our exceptional engineers and drug discovery experts to bring complex ideas to life. We also want you to be a voice in the scientific community. We will actively support and champion your efforts to publish some research breakthroughs in premier ML venues such as NeurIPS, ICML, and ICLR.
Positions are available at various levels of seniority: Senior, Staff, and 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.

About Genesis Molecular AI
Genesis Molecular AI is pioneering foundation models for molecular AI to unlock a new era of drug design and development. Our generative and predictive AI platform, GEMS (Genesis Exploration of Molecular Space), integrates AI and physics into industry-leading models to generate and optimize drug molecules, including the breakthrough generative diffusion model Pearl for structure prediction. Genesis is backed by premier AI and life science investors, including a16z, NVIDIA, Rock Springs Capital, Menlo Ventures, T. Rowe Price, Fidelity, and Radical Ventures. Genesis has also signed category-leading AI-pharma deals, the most recent of which was a significant expansion with Incyte (see coverage in Forbes and GEN) with a total potential deal value of several billion dollars.
Genesis is headquartered in San Mateo, 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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