Manager, New Product Planning
Location
San Diego, CA
Employment Type
Full time
Location Type
Hybrid
Department
G&A
Compensation
$85K – $115K • Offers Equity • Offers Bonus
Overview
Application
The New Product Planning Manager is a high impact role that will support the strategy, planning and execution of commercial assessments for Genesis’s AI-enabled pipeline programs. The position will report to the Director of New Product Planning.
This role will be hybrid 2-3 days a week based at Genesis’s San Diego office.
Key Responsibilities:
Market analysis: Analyze disease areas, treatment paradigms, and unmet needs to help shape the positioning of new potential drugs
Primary and secondary research: Support KOL interviews, along with secondary research such as epidemiology and published literature, to build and validate commercial assumptions
Competitive monitoring: Track competitor pipelines, clinical readouts, approvals, and deals, including monitoring conference abstracts and presentations for early signals, and translate the implications into updated assumptions for the team
Development strategy: Contribute commercial input into Target Product Profiles (TPPs) and clinical development plans (endpoints, comparators, patient populations, and indication sequencing)
Cross-functional collaboration: Work with discovery, preclinical development, business development, and finance to keep programs aligned with commercial objectives
Candidate profile:
Life sciences background, ideally a BS or MS degree in biology or a related field
1-2 years at a top-tier consulting firm, investment bank, or equity research group preferred
Experience in New Product Planning, marketing, portfolio strategy, competitive intelligence, or a related analytical role at a pharmaceutical or biotech company also considered
Experience in oncology or immunology is a plus
Some exposure to commercial assessments based on primary and secondary research, ideally for preclinical and early clinical assets
Strong Excel modeling and PowerPoint skills
Excellent communication, listening, and presentation skills
Ability to travel domestically and internationally, if required, approximately 10% of the time
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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Listed by Genesis Molecular AI for a position based in the United States. Employers on this board attest they are hiring domestically.
ML & Molecular Simulation Scientist
Location
San Mateo, CA
Employment Type
Full time
Department
AI
Overview
Application
About the Team
At Genesis Molecular AI, we're a tight-knit team of deep learning researchers, computational scientists, and drug discovery pioneers united by a single mission: to develop the next generation of AI-driven therapies for patients with severe diseases.
We don't just apply machine learning to biology – we conduct fundamental research at the intersection of machine learning, physics, and computational chemistry, pushing the boundaries of each field.
At Genesis, simulation and machine learning aren't separate disciplines: they're deeply integrated, and the scientists who do this work sit at the center of everything we build. You will work side by side with world-class researchers across ML, chemistry, and biology, with access to large-scale compute infrastructure and simulation pipelines, contributing to a platform where physics-based methods and AI advance together.
About the Role
We are seeking a ML & Molecular Simulation Scientist to develop and apply methods at the intersection of 3D molecular simulation and machine learning, and see those methods through to real impact in drug discovery programs.
This is a role for someone who thrives at the intersection of computational science and machine learning: designing and running simulations, building ML models grounded in physical intuition, and collaborating directly with CADD and discovery teams to move molecules from hit identification to lead optimization.
Some areas you may focus on:
Build and apply ML models informed by 3D structural data, including geometric deep learning, equivariant neural networks, and diffusion-based generative models for molecular design and property prediction
Integrate physics-based and ML + data-driven approaches, combining force field methods, quantum chemistry, and structure-based design with modern ML to improve accuracy and throughput
Develop and apply simulation methods spanning molecular dynamics, enhanced sampling (metadynamics, replica exchange, umbrella sampling), and free energy calculations (FEP/TI) to support active drug discovery programs
Contribute to the GEMS platform, improving our generative AI and scoring capabilities, focusing on 3D methods; strengthen ML and physics-based scoring functions (and their intersection), build next-gen force fields
Work directly with CADD and discovery scientists to apply computational methods across the drug discovery pipeline, from target structure analysis through lead optimization
Stay current with the field, implementing and adapting methods from the latest literature in geometric ML, biomolecular simulation, and computational drug design
Communicate scientific results clearly to multidisciplinary teams, including experimental chemists and biologists
Who You Are
Practical experience with 3D machine learning – geometric deep learning, graph neural networks, equivariant architectures (e.g., SE(3)/E(3) networks), or diffusion models applied to molecular data
PhD (preferred) in computer science, machine learning, chemical engineering, biophysics, physics, or a closely related field; postdoctoral or industry experience is a plus
Deep, hands-on expertise in molecular simulation, including MD, enhanced sampling, and/or free energy methods using tools such as GROMACS, AMBER, OpenMM, or NAMD
Familiarity with structure-based drug design workflows: docking, binding site analysis, protein-ligand interaction modeling using tools such as MOE, or PyMOL
Proficiency in Python and scientific computing libraries (PyTorch, JAX, NumPy, MDAnalysis, RDKit); comfort with HPC environments and scripting for large-scale simulation workflows
A track record of applying computational methods to real scientific problems, demonstrated through publications, open-source contributions, or industry impact
Collaborative, curious, and able to move between rigorous method development and fast-paced discovery work
Nice to Have
Familiarity with cheminformatics and ADMET property prediction
Contributions to open-source simulation or ML tooling
What We Offer
Highly competitive compensation including base, bonus, and equity
Comprehensive health, dental, and vision insurance (fully covered for employees)
Stock option eligibility
401(k) plan
Open PTO policy
Paid company holidays
Daily meals and snacks in the office
Flexible work environment
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.
Apply for this Job
Powered by
Privacy PolicySecurityVulnerability Disclosure
Listed by Genesis Molecular AI for a position based in the United States. Employers on this board attest they are hiring domestically.
About the Team
At Genesis Molecular AI, we're a tight-knit team of deep learning researchers, computational scientists, and drug discovery pioneers united by a single mission: to develop the next generation of AI-driven therapies for patients with severe diseases.
We don't just apply machine learning to biology – we conduct fundamental research at the intersection of machine learning, physics, and computational chemistry, pushing the boundaries of each field.
At Genesis, simulation and machine learning aren't separate disciplines: they're deeply integrated, and the scientists who do this work sit at the center of everything we build. You will work side by side with world-class researchers across ML, chemistry, and biology, with access to large-scale compute infrastructure and simulation pipelines, contributing to a platform where physics-based methods and AI advance together.
About the Role
We are seeking a ML & Molecular Simulation Scientist to develop and apply methods at the intersection of 3D molecular simulation and machine learning, and see those methods through to real impact in drug discovery programs.
This is a role for someone who thrives at the intersection of computational science and machine learning: designing and running simulations, building ML models grounded in physical intuition, and collaborating directly with CADD and discovery teams to move molecules from hit identification to lead optimization.
Some areas you may focus on:
- Build and apply ML models informed by 3D structural data, including geometric deep learning, equivariant neural networks, and diffusion-based generative models for molecular design and property prediction
- Integrate physics-based and ML + data-driven approaches, combining force field methods, quantum chemistry, and structure-based design with modern ML to improve accuracy and throughput
- Develop and apply simulation methods spanning molecular dynamics, enhanced sampling (metadynamics, replica exchange, umbrella sampling), and free energy calculations (FEP/TI) to support active drug discovery programs
- Contribute to the GEMS platform, improving our generative AI and scoring capabilities, focusing on 3D methods; strengthen ML and physics-based scoring functions (and their intersection), build next-gen force fields
- Work directly with CADD and discovery scientists to apply computational methods across the drug discovery pipeline, from target structure analysis through lead optimization
- Stay current with the field, implementing and adapting methods from the latest literature in geometric ML, biomolecular simulation, and computational drug design
- Communicate scientific results clearly to multidisciplinary teams, including experimental chemists and biologists
Who You Are
- Practical experience with 3D machine learning – geometric deep learning, graph neural networks, equivariant architectures (e.g., SE(3)/E(3) networks), or diffusion models applied to molecular data
- PhD (preferred) in computer science, machine learning, chemical engineering, biophysics, physics, or a closely related field; postdoctoral or industry experience is a plus
- Deep, hands-on expertise in molecular simulation, including MD, enhanced sampling, and/or free energy methods using tools such as GROMACS, AMBER, OpenMM, or NAMD
- Familiarity with structure-based drug design workflows: docking, binding site analysis, protein-ligand interaction modeling using tools such as MOE, or PyMOL
- Proficiency in Python and scientific computing libraries (PyTorch, JAX, NumPy, MDAnalysis, RDKit); comfort with HPC environments and scripting for large-scale simulation workflows
- A track record of applying computational methods to real scientific problems, demonstrated through publications, open-source contributions, or industry impact
- Collaborative, curious, and able to move between rigorous method development and fast-paced discovery work
Nice to Have
- Familiarity with cheminformatics and ADMET property prediction
- Contributions to open-source simulation or ML tooling
What We Offer
- Highly competitive compensation including base, bonus, and equity
- Comprehensive health, dental, and vision insurance (fully covered for employees)
- Stock option eligibility
- 401(k) plan
- Open PTO policy
- Paid company holidays
- Daily meals and snacks in the office
- Flexible work environment
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.
About the Team
At Genesis Molecular AI, we're a tight-knit team of deep learning researchers, computational scientists, and drug discovery pioneers united by a single mission: to develop the next generation of AI-driven therapies for patients with severe diseases.
We don't just apply machine learning to biology – we conduct fundamental research at the intersection of machine learning, physics, and computational chemistry, pushing the boundaries of each field.
At Genesis, simulation and machine learning aren't separate disciplines: they're deeply integrated, and the scientists who do this work sit at the center of everything we build. You will work side by side with world-class researchers across ML, chemistry, and biology, with access to large-scale compute infrastructure and simulation pipelines, contributing to a platform where physics-based methods and AI advance together.
About the Role
We are seeking a ML & Molecular Simulation Scientist to develop and apply methods at the intersection of 3D molecular simulation and machine learning, and see those methods through to real impact in drug discovery programs.
This is a role for someone who thrives at the intersection of computational science and machine learning: designing and running simulations, building ML models grounded in physical intuition, and collaborating directly with CADD and discovery teams to move molecules from hit identification to lead optimization.
Some areas you may focus on:
- Build and apply ML models informed by 3D structural data, including geometric deep learning, equivariant neural networks, and diffusion-based generative models for molecular design and property prediction
- Integrate physics-based and ML + data-driven approaches, combining force field methods, quantum chemistry, and structure-based design with modern ML to improve accuracy and throughput
- Develop and apply simulation methods spanning molecular dynamics, enhanced sampling (metadynamics, replica exchange, umbrella sampling), and free energy calculations (FEP/TI) to support active drug discovery programs
- Contribute to the GEMS platform, improving our generative AI and scoring capabilities, focusing on 3D methods; strengthen ML and physics-based scoring functions (and their intersection), build next-gen force fields
- Work directly with CADD and discovery scientists to apply computational methods across the drug discovery pipeline, from target structure analysis through lead optimization
- Stay current with the field, implementing and adapting methods from the latest literature in geometric ML, biomolecular simulation, and computational drug design
- Communicate scientific results clearly to multidisciplinary teams, including experimental chemists and biologists
Who You Are
- Practical experience with 3D machine learning – geometric deep learning, graph neural networks, equivariant architectures (e.g., SE(3)/E(3) networks), or diffusion models applied to molecular data
- PhD (preferred) in computer science, machine learning, chemical engineering, biophysics, physics, or a closely related field; postdoctoral or industry experience is a plus
- Deep, hands-on expertise in molecular simulation, including MD, enhanced sampling, and/or free energy methods using tools such as GROMACS, AMBER, OpenMM, or NAMD
- Familiarity with structure-based drug design workflows: docking, binding site analysis, protein-ligand interaction modeling using tools such as MOE, or PyMOL
- Proficiency in Python and scientific computing libraries (PyTorch, JAX, NumPy, MDAnalysis, RDKit); comfort with HPC environments and scripting for large-scale simulation workflows
- A track record of applying computational methods to real scientific problems, demonstrated through publications, open-source contributions, or industry impact
- Collaborative, curious, and able to move between rigorous method development and fast-paced discovery work
Nice to Have
- Familiarity with cheminformatics and ADMET property prediction
- Contributions to open-source simulation or ML tooling
What We Offer
- Highly competitive compensation including base, bonus, and equity
- Comprehensive health, dental, and vision insurance (fully covered for employees)
- Stock option eligibility
- 401(k) plan
- Open PTO policy
- Paid company holidays
- Daily meals and snacks in the office
- Flexible work environment
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.
Genesis Molecular AI is pioneering the use of AI and biophysics to transform drug discovery. Backed by leading investors such as a16z, NVIDIA (via NVentures) and Radical Ventures, we are growing thoughtfully and deliberately to build one of the most talented research and engineering teams in the world.
We are seeking a Staff Technical Recruiter to own full-cycle hiring for our AI/ML research and engineering organization. This is a high-impact individual contributor role working with our Head of Recruiting and technical leadership to bring exceptional talent into Genesis.
What You'll Do
Own searches end-to-end across AI/ML research and engineering, from sourcing and outreach through offer and close
Build deep knowledge of our technical roles and the competitive talent landscape to move quickly and effectively on top candidates
Design and run our intern and new graduate hiring programs, including university partnerships, research lab relationships, and on-campus recruiting: build a repeatable, scalable process that consistently converts early career talent into future full-time hires
Proactively map and continuously engage the global pool of top AI/ML researchers and engineers relevant to our domain, and cultivate long-term relationships so Genesis is top of mind when exceptional researchers consider their next move
Represent Genesis at key venues (e.g. NeurIPS, ICML, ICLR) and build sustained relationships with faculty, PhD students, and postdocs at top research universities
Champion an outstanding candidate experience throughout the process. Close candidates with the right balance of transparency, enthusiasm, and persistence.
Track pipeline health and recruiting metrics in Ashby. Identify bottlenecks and continuously improve your own workflows for efficiency and impact.
What You Bring
5+ years of full-cycle technical recruiting experience, with a meaningful focus on AI/ML or research roles
A track record of sourcing and closing niche technical talent in competitive markets
Experience running or contributing to university/early career programs, including internship pipelines
Comfort building proactive sourcing strategies and maintaining long-term candidate relationships, not just reactive hiring
Familiarity with the AI/ML research community: key conferences, institutions, labs, and publication venues
Data fluency and experience with modern ATS tools (Ashby experience a plus)
Comfortable owning projects end-to-end, from initial concept through execution, while staying adaptable when priorities change quickly
Strong interpersonal skills and the ability to build trust with researchers and engineers who are skeptical of recruiting processes
Biotech background not required: curiosity and fast learning are highly valued
What We Offer
Competitive compensation package including salary and equity
Comprehensive health benefits: Medical, Dental, and Vision (covered 100% for employees)
401(k) plan
Open (unlimited) PTO policy
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.
Genesis Molecular AI is building a world-class software team to solve problems in drug discovery through machine learning, biophysical simulation, and computational chemistry. We are looking for engineers excited to help develop new medicines and play a critical role in building out our software platform.
You will
Own and evolve the full-stack platform that computational chemists use daily, from data exploration and experiment management to real-time visualization, shipping AI-native workflows and modern interaction patterns that shorten the loop between hypothesis and insight
Build and expand tools for visualizing molecules and proteins, analyzing ML models, and managing complex chemical workflows
Partner with machine learning engineers and computational chemists to develop and productionize new computational methods for molecular property prediction
Scale our data infrastructure to handle billions of datapoints and thousands of parallel deep learning and molecular dynamics jobs
You are
A deep thinker who reasons from first principles, balances attention to detail with architectural thinking, and has an investigative curiosity to find the root cause of a problem
Comfortable owning problems across the entire stack — frontend interfaces, backend services, data pipelines, and infrastructure
Experienced shipping production code and driving projects end-to-end with minimal hand-holding
Excited to work at the intersection of software engineering, drug discovery, and machine learning
What we offer
The opportunity to work on high impact tools and products that are immediately deployed to accelerate the discovery of new medicines
Strong technical coworkers in AI, software, and chemistry, who all have a powerful mix of intellectual curiosity and humility. The team reads and discusses 1-2 machine learning or chemistry papers every week to stay on top of the field and inspire new ideas
Competitive salary and equity. Medical, dental, and vision insurance, and a 401(k) program
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.
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