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Research Scientist, Condensed Matter Theory
Periodic Labs · United States, United States
$225k–325k
301 days ago
♡
Research Scientist, Condensed Matter Theory
Periodic Labs · United States, United States
$225k–325k
301 days ago
♡
Staff ML Research Scientist
Rad AI · San Francisco, California, United States
$190k–260k
328 days ago
♡
ML Research Scientist, Foundation Models (Senior / Staff / Principal)
Genesis Molecular AI ·
$120k–245k
406 days ago
♡
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Principal Scientist, Biologics
Boltz · London
Pay
Not listed
Setting
Remote
Listed by Boltz for a position based in the United States. Employers on this board attest they are hiring domestically.
Member of Technical Staff, Research Engineer
RunwayML · United States
Pay
$270k–370k
Setting
Remote
We are building AI to simulate the world through merging art and science.
We believe that world models are at the frontier of progress in artificial intelligence. Language models alone won’t solve the world’s hardest problems – robotics, disease, scientific discovery. Real progress requires models that experience the world and learn from their mistakes, the same way that humans do. And this kind of trial and error can be massively accelerated when done in simulation, rather than in the real world.
World models offer the most clear path to general-purpose simulation, changing how stories are told, how scientific progress is made and how the next frontiers of humanity are reached.
Our team consists of creative, open minded, caring and ambitious people who are determined to change the world. We aspire to continuously build impossible things and our ability to do so relies on building an incredible team. If you are driven to do the same, we'd love to hear from you.
ABOUT THE ROLE
We’re looking for Research Engineers to contribute to our ambitious research agenda spanning multimodal foundational models, interactive world modeling, and real-time generation. This role is highly collaborative and will touch many aspects of our broader research efforts, taking a full-stack approach across pretraining, SFT/RL post-training techniques, evaluation, and bringing models to production.
WHAT YOU’LL DO
- Run experiments to teach world models new behaviors — action following, scene manipulation, camera control, and beyond
- Develop and test new data strategies, architectural variants, and training techniques
- Design evaluations that measure model capabilities, and use them to drive model improvement
- Take features from research prototype to production, collaborating with product and creative teams to address application-specific gaps
- Contribute across the entire stack (data pipelines, modeling, production inference) to move projects forward
WHAT YOU’LL NEED
- 4+ years of experience in machine learning research or engineering
- Familiarity with the architecture, training, and inference of large-scale multimodal generative models
- Experience building robust data pipelines for pretraining and post-training
- Comfort working across the full research stack: data, training, evaluation, and deployment
- Proficiency with at least one ML framework (e.g. PyTorch, JAX) and experience with distributed training at scale
- Ability to context-switch quickly and drive projects forward in a fast-moving, ambiguous environment
- Excitement about building AI that simulates the world
Runway strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team. Our salary ranges are based on competitive market rates for our size, stage and industry, and salary is just one part of the overall compensation package we provide.
There are many factors that go into salary determinations, including relevant experience, skill level and qualifications assessed during the interview process, and maintaining internal equity with peers on the team. The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more or less experienced than outlined in the job description. In this case, we will communicate any updates in the expected salary range.
Lastly, the provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range, which again, will be communicated to candidates.
WORKING AT RUNWAY
Great things come from great teams. https://www.youtube.com/watch?v=kwmj4ato2kw&ab_channel=Runway We’d love to hear from you.
We’re committed to creating a space where our employees can bring their full selves to work and have equal opportunity to succeed. So regardless of race, gender identity or expression, sexual orientation, religion, origin, ability, age, veteran status, if joining this mission speaks to you, we encourage you to apply.
More about Runway
- Universal World Simulator https://runwayml.com/world-simulator.html
- GWM-1 https://runwayml.com/research/introducing-runway-gwm-1
- Gen-4.5 https://runwayml.com/research/introducing-runway-gen-4.5
- General World Models https://runwayml.com/research/introducing-general-world-models
- Robotics SDK https://runwayml.com/research/introducing-runway-gwm-1#robotics-section
- Conversational Real-time Agents https://runwayml.com/research/introducing-runway-gwm-1#avatars-section
- Runway Studios https://runwayml.com/studios
We're excited to be recognized as a best place to work:
Crain's https://www.crainsnewyork.com/awards/best-places-work-2023 | InHerSight https://www.inhersight.com/companies/best/city/new-york-city-ny | BuiltIn NYC https://builtin.com/awards/new-york-city/2024/best-places-to-work | INC https://www.inc.com/best-workplaces/2024
Listed by RunwayML for a position based in the United States. Employers on this board attest they are hiring domestically.
Research Scientist, Condensed Matter Theory
Periodic Labs · United States
Pay
$225k–325k
Setting
Remote
Research Scientist, Condensed Matter Theory
Location
United States
Address
United States
Employment Type
Full time
Location Type
Remote
Department
Science
Overview
Application
About Periodic Labs
We’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.
About the Role
Join a world-class team of scientists and engineers pushing the boundaries of physics research in a groundbreaking lab where AI, theory, and automation unlock discoveries at unprecedented speed and scale.
As a Research Scientist in Condensed Matter Theory, you will use theoretical modeling to connect first-principles calculations and experiments. You will collaborate closely with computational and experimental scientists and ML researchers to develop physical understanding that guides and accelerates the discovery of novel quantum materials.
What You’ll Do
Develop and apply theoretical models to interpret experimental observations and guide materials discovery efforts
Bridge first-principles calculations (e.g., DFT) and experimental results to build predictive physical understanding
Collaborate with ML researchers to incorporate theoretical insights into machine learning models and inform training data strategies
Work with computational and experimental scientists to design experiments and validate theoretical predictions
Communicate theoretical findings clearly across disciplines and contribute to a shared scientific roadmap
You Will Thrive in This Role If You Have
PhD in condensed matter theory, with a focus on quantum materials
Deep expertise in relating theoretical models to real materials and experimental observables
Strong publication record demonstrating impactful, independent research
Ability to collaborate effectively across theory, computation, and experiment
Especially Strong Candidates May Also Have
Experience running first-principles calculations such as density functional theory (DFT) on realistic systems
Experience with deep learning methods, including graph neural networks, applied to materials or physics problems
Experience modeling superconductivity and/or magnetism in quantum materials
Familiarity with high-throughput computational workflows or materials databases
Mechanics
Minimum education: Bachelor’s degree or similar experience
Location: Menlo Park, CA or Montreal, Canada. (Soon: San Francisco, too)
Compensation: $225,000–$325,000 + equity
Visa sponsorship: Yes, we sponsor visas.
We’re building a team of the world’s best — the scientists, engineers, and problem-solvers who don’t just follow the frontier, they define it. If you’re driven to bring AI to life in the physical world and make discoveries that have never been made before, you belong here.
Apply for this Job
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Listed by Periodic Labs for a position based in the United States. Employers on this board attest they are hiring domestically.
Research Scientist, Condensed Matter Theory
Periodic Labs · United States, United States
Pay
$225k–325k
Setting
Remote
About Periodic Labs
We’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.
About the Role
Join a world-class team of scientists and engineers pushing the boundaries of physics research in a groundbreaking lab where AI, theory, and automation unlock discoveries at unprecedented speed and scale.
As a Research Scientist in Condensed Matter Theory, you will use theoretical modeling to connect first-principles calculations and experiments. You will collaborate closely with computational and experimental scientists and ML researchers to develop physical understanding that guides and accelerates the discovery of novel quantum materials.
What You’ll Do
Develop and apply theoretical models to interpret experimental observations and guide materials discovery efforts
Bridge first-principles calculations (e.g., DFT) and experimental results to build predictive physical understanding
Collaborate with ML researchers to incorporate theoretical insights into machine learning models and inform training data strategies
Work with computational and experimental scientists to design experiments and validate theoretical predictions
Communicate theoretical findings clearly across disciplines and contribute to a shared scientific roadmap
You Will Thrive in This Role If You Have
PhD in condensed matter theory, with a focus on quantum materials
Deep expertise in relating theoretical models to real materials and experimental observables
Strong publication record demonstrating impactful, independent research
Ability to collaborate effectively across theory, computation, and experiment
Especially Strong Candidates May Also Have
Experience running first-principles calculations such as density functional theory (DFT) on realistic systems
Experience with deep learning methods, including graph neural networks, applied to materials or physics problems
Experience modeling superconductivity and/or magnetism in quantum materials
Familiarity with high-throughput computational workflows or materials databases
Mechanics
Minimum education: Bachelor’s degree or similar experience
Location: Menlo Park, CA or Montreal, Canada. (Soon: San Francisco, too)
Compensation: $225,000–$325,000 + equity
Visa sponsorship: Yes, we sponsor visas.
We’re building a team of the world’s best — the scientists, engineers, and problem-solvers who don’t just follow the frontier, they define it. If you’re driven to bring AI to life in the physical world and make discoveries that have never been made before, you belong here.
Listed by Periodic Labs for a position based in the United States. Employers on this board attest they are hiring domestically.
Research Scientist, Condensed Matter Theory
Periodic Labs · United States, United States
Pay
$225k–325k
Setting
Remote
ABOUT PERIODIC LABS
We’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.
ABOUT THE ROLE
Join a world-class team of scientists and engineers pushing the boundaries of physics research in a groundbreaking lab where AI, theory, and automation unlock discoveries at unprecedented speed and scale.
As a Research Scientist in Condensed Matter Theory, you will use theoretical modeling to connect first-principles calculations and experiments. You will collaborate closely with computational and experimental scientists and ML researchers to develop physical understanding that guides and accelerates the discovery of novel quantum materials.
WHAT YOU’LL DO
- Develop and apply theoretical models to interpret experimental observations and guide materials discovery efforts
- Bridge first-principles calculations (e.g., DFT) and experimental results to build predictive physical understanding
- Collaborate with ML researchers to incorporate theoretical insights into machine learning models and inform training data strategies
- Work with computational and experimental scientists to design experiments and validate theoretical predictions
- Communicate theoretical findings clearly across disciplines and contribute to a shared scientific roadmap
YOU WILL THRIVE IN THIS ROLE IF YOU HAVE
- PhD in condensed matter theory, with a focus on quantum materials
- Deep expertise in relating theoretical models to real materials and experimental observables
- Strong publication record demonstrating impactful, independent research
- Ability to collaborate effectively across theory, computation, and experiment
ESPECIALLY STRONG CANDIDATES MAY ALSO HAVE
- Experience running first-principles calculations such as density functional theory (DFT) on realistic systems
- Experience with deep learning methods, including graph neural networks, applied to materials or physics problems
- Experience modeling superconductivity and/or magnetism in quantum materials
- Familiarity with high-throughput computational workflows or materials databases
MECHANICS
Minimum education: Bachelor’s degree or similar experience
Location: Menlo Park, CA or Montreal, Canada. (Soon: San Francisco, too)
Compensation: $225,000–$325,000 + equity
Visa sponsorship: Yes, we sponsor visas.
We’re building a team of the world’s best — the scientists, engineers, and problem-solvers who don’t just follow the frontier, they define it. If you’re driven to bring AI to life in the physical world and make discoveries that have never been made before, you belong here.
Listed by Periodic Labs for a position based in the United States. Employers on this board attest they are hiring domestically.
Research Scientist
Snorkel AI · Redwood City, CA (Hybrid)
Pay
$200k–350k
Setting
Remote
Listed by Snorkel AI for a position based in the United States. Employers on this board attest they are hiring domestically.
Staff ML Research Scientist
Rad AI · San Francisco, California, United States
Pay
$190k–260k
Setting
Remote
ABOUT RAD AI
At Rad AI, we’re on a mission to transform healthcare with artificial intelligence. Founded by a radiologist, our AI-driven solutions are revolutionizing radiology—saving time, reducing burnout, and improving patient care. With one of the largest proprietary radiology report datasets in the world, our AI has helped uncover hundreds of new cancer diagnoses and reduced error rates in tens of millions of radiology reports by nearly 50%.
Rad AI has secured over $140M in funding, including a recently oversubscribed Series C ($68M round) led by Transformation Capital, bringing our valuation to $528M. Our investors include Khosla Ventures, World Innovation Lab, Gradient Ventures, Cone Health Ventures, and others—all backing our mission to empower physicians with cutting-edge AI.
Our latest advancements in generative AI are used by thousands of radiologists daily, supporting more than one-third of radiology groups and healthcare systems and nearly 50% of all medical imaging in the U.S. at partners including Cone Health, Jefferson Einstein Health, Geisinger, Guthrie Healthcare System, and Henry Ford Health.
Recognized as one of the most promising healthcare AI companies by CB Insights and AuntMinnie https://www.radai.com/news/auntminnie-recognizes-rad-ai-omni-reporting-as-2023s-best-new-radiology-software, and ranked by Deloitte https://www2.deloitte.com/us/en/pages/technology-media-and-telecommunications/articles/fast500-winners.html as the 19th fastest-growing company in North America, we are building AI-powered solutions that make a real impact. Most recently, Rad AI was named to CNBC’s Disruptor 50 https://www.cnbc.com/2025/06/10/2025-cnbc-disruptor-50-see-the-full-list-of-companies.html list, highlighting the innovation and momentum behind our mission.
If you’re ready to shape the future of healthcare, we’d love to have you on our team!
Why Join Us?
We're looking for a Staff Machine Learning Research Scientist to help define and drive Rad AI's next generation of applied research in NLP and clinical AI.
We work across LLMs, retrieval, representation learning, speech and multimodal modeling, and we care as much about evaluation and reliability as we do about state-of-the-art results. You will have scope, ownership, and a direct line from research to product.
You'll collaborate closely with clinicians, engineers, and product leaders to translate foundational research into production-scale systems that improve outcomes for doctors and patients alike. As we grow, you will help shape standards for model quality, safety, and observability, and contribute to strategic initiatives that include computer vision and vision-language work.
What You'll Do:
- Own end-to-end applied research: frame the problem, design experiments, ship to production, and monitor impact against real-world metrics.
- Set technical direction across LLMs, retrieval, and multimodal; run ablations/error analysis that change product decisions.
- Build evaluation that matters: link offline metrics to online outcomes; define thresholds, monitoring, and rollback.
- Partner to deliver with engineering and product—and, when relevant, clinicians/domain experts—to align data, success criteria, and timelines.
- Raise the bar by mentoring peers and codifying standards for reliability, safety, and documentation.
- Improve the platform (data, training, serving, observability) to speed iteration and ensure reproducibility.
- Explore new directions, with computer vision/vision-language work as a nice-to-have for future strategic initiatives.
What We're Looking For:
- MS or PhD (or equivalent research experience) in Computer Science, Electrical Engineering, Computational Linguistics, Biomedical Informatics, or related quantitative field.
- 7+ years of applied ML research experience (or PhD + 5 years, or equivalent evidence of Staff-level impact).
- Depth in one or more areas: LLMs and NLP, computer vision, speech, recommendation/ranking, retrieval, or multimodal modeling.
- Strong experimental rigor: clear hypothesis framing, offline→online linkage, calibration and stratified analyses, ablations that influence decisions.
- Proven ability to take models to production
- Hands-on with modern tooling: PyTorch and common experiment/ops tools (for example MLflow, Databricks, Ray, or similar).
- System thinking: can choose methods based on constraints, design for observability and rollback, and document decisions clearly.
- Collaborative communicator who writes crisp design docs and explains complex ideas to non-specialists; comfortable mentoring peers.
Preferred Qualifications
- Health data familiarity, including EHR or imaging
- Experience in one or more areas: clinical NLP or LLMs, computer vision, speech, retrieval or multimodal modeling.
- Shipped, measured models in production with monitoring and clear rollback; external or multi-site validation is a plus.
- Workflow integration with EHR, RIS, PACS, or reporting systems; PowerScribe or Dragon exposure helpful.
- Strong evaluation practices: calibration, slice analysis, and ablations
- Safety and governance in sensitive domains, including PHI handling and HIPAA or FDA-adjacent environments.
- Technical mentorship and contributions to team research culture; publications or impactful open-source work.
- Practical tooling: PyTorch plus modern ML ops tools such as MLflow, Databricks, Ray, or Triton.
Why This Matters:
Radiologists are the invisible backbone of modern medicine. Every diagnosis, every surgery, every treatment plan begins with their interpretations. Yet they're often overwhelmed by cognitive load, repetitive tasks, and administrative overhead.
At Rad AI, we're using ML to change that—building intelligent systems that understand medical context, streamline documentation, and amplify human expertise.
You've already seen how AI can transform healthcare. Now help us push it further.
Join us in shaping how AI supports the next generation of medical professionals.
We welcome applicants from across the United States, with a preference for this role to be based in our new San Francisco office.
Join our world-class team as we build and deploy AI solutions that empower physicians and transform patient care—making a meaningful impact on millions of lives. Driven by our mission, we prioritize transparency, inclusion, and close collaboration, bringing together exceptional people to revolutionize healthcare. If you're passionate about driving innovation and delivering impactful healthcare solutions, we'd love to hear from you!
To learn more about what it's like to work at Rad AI, visit https://www.radai.com/life-at-rad-ai and be sure to follow us on LinkedIn https://www.linkedin.com/company/radai/?utm_campaign=Recruiting_2026&utm_content=recruiting-job-posting-website&utm_source=recru%5B%E2%80%A6%5Db-posting-website to stay up to date!
For US-Based Full-Time Roles, Rad AI offers a variety of benefits, including:
- Comprehensive Medical, Dental, Vision & Life insurance
- HSA (with employer match), FSA, & DCFSA
- 401(k)
- 11 Paid Company Holidays
- Flexible PTO policy
- Annual company-wide offsite
- Periodic team offsites
- Annual equipment stipend
- For roles based outside the US, your recruiter can share more details
At Rad AI, we value diversity and provide equal employment opportunities (EEO) to all employees and applicants without regard to race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.
Please be vigilant regarding job scams. We advise all candidates to apply directly through our official careers page. Our recruiters will use email addresses with the domain @radai.com http://radai.com or no-reply@ashbyhq.com.
Listed by Rad AI for a position based in the United States. Employers on this board attest they are hiring domestically.
ML Research Scientist, Foundation Models (Senior / Staff / Principal)
Genesis Molecular AI ·
Pay
$120k–245k
Setting
Remote
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
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 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.
Listed by Genesis Molecular AI for a position based in the United States. Employers on this board attest they are hiring domestically.
ML Research Scientist, Foundation Models (Senior / Staff / Principal)
Genesis Molecular AI ·
Pay
$120k–245k
Setting
Remote
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 http://genesis.ml 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 https://www.businesswire.com/news/home/20251028030745/en/Genesis-Molecular-AI-Unveils-Pearl-a-Field-Leading-Foundation-Model-that-Achieves-Unprecedented-Performance-in-Drug-Protein-Structure-Prediction 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 https://www.forbes.com/sites/innovationrx/2026/05/20/inside-incytes-120-million-ai-for-drug-development-deal/ and GEN https://www.genengnews.com/topics/artificial-intelligence/small-molecules-to-big-partnership-incyte-genesis-expand-ai-collaboration-to-1b/) 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.
Listed by Genesis Molecular AI for a position based in the United States. Employers on this board attest they are hiring domestically.
ML Research Scientist, Foundation Models (Senior / Staff / Principal)
Genesis Molecular AI ·
Pay
$120k–245k
Setting
Remote
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 http://genesis.ml 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 https://www.businesswire.com/news/home/20251028030745/en/Genesis-Molecular-AI-Unveils-Pearl-a-Field-Leading-Foundation-Model-that-Achieves-Unprecedented-Performance-in-Drug-Protein-Structure-Prediction 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 https://www.forbes.com/sites/innovationrx/2026/05/20/inside-incytes-120-million-ai-for-drug-development-deal/ and GEN https://www.genengnews.com/topics/artificial-intelligence/small-molecules-to-big-partnership-incyte-genesis-expand-ai-collaboration-to-1b/) 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.
Listed by Genesis Molecular AI for a position based in the United States. Employers on this board attest they are hiring domestically.
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