Genesis Molecular AI jobs

Intellectual Property (IP) Counsel Remote Genesis Molecular AI's legal team is small by design and central to the company's success. As the second attorney in the department, you will work directly alongside the Head of Legal on the full range of matters that keep a growth-stage, venture-backed company running, from building the IP portfolio that protects our core platform and drug discovery programs to negotiating the commercial agreements that fuel our growth. At a company like Genesis, where the work spans cutting-edge AI, computational chemistry, and drug development, legal is not a back-office function. You will be embedded with the research, engineering, and business teams, engaging on strategic questions early and often. The legal team operates with the same values as the rest of Genesis: interdisciplinary curiosity, ownership, and a bias toward impact. You will have real responsibility from day one, a direct line to leadership, and the opportunity to help shape the legal foundation of a company doing genuinely important work. About The Role: We are looking for an Intellectual Property (IP) Counsel to join our growing legal team as our second in-house attorney. Your primary responsibilities will be to build and protect Genesis's intellectual property portfolio, which spans our AI platform, foundation models, and small molecular drug discovery programs. You will be responsible for helping to develop our patenting strategy, leading patent harvesting sessions with inventors, helping to draft claims, and working with outside counsel to file and prosecute applications. Beyond patents, we are looking for someone that

Staff Technical Recruiter San Mateo, CA 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.

Senior Director, Medicinal Chemistry San Diego, CA The successful candidate will utilize the Genesis Molecular AI platform and guide medicinal chemistry efforts to drug discovery programs from Hit ID through candidate nomination. They will collaborate and/or lead multidisciplinary drug discovery projects and be responsible for shaping medicinal chemistry strategy on those projects. The candidate will be expected to be a medicinal chemistry leader and strong communicator. What You Will Do (Key Responsibilities) - Formulate medicinal chemistry strategies and utilize the Genesis platform to execute drug discovery programs from Hit ID through candidate nomination. - Use Structure-Based Drug Design (SBDD) principles, optimize physiochemical properties, interpret in vitro and in vivo ADME/PK/Toxicology data, and understand in vitro and in vivo biology data to drive programs. - Use data visualization software and metric based analysis to form medicinal chemistry hypotheses and prioritize strategies. - Communicate and work with industry collaborators on drug discovery projects. - Work with other drug discovery disciplines (biology, DMPK, software engineers, computational chemists) to drive hypothesis driven decisions, improve the platform and contribute to the scientific excellence of the company. - Communicate and engage regularly with project team members and management. - Mentor internal chemists as well as other scientific disciplines on medicinal chemistry principles. What you'll bring - PhD in synthetic organic chemistry or medicinal chemistry with at least 12 years of industrial drug discovery experience OR - MS in synthetic organic chemistry with at least 18 years of industrial drug discovery experience. - Expert medicinal chemistry knowledge

Product Management Lead San Mateo, CA, New York, NY, Remote, San Diego, CA Genesis Molecular AI is pioneering a transformative approach to drug discovery by leveraging state-of-the-art machine learning, computational chemistry, and biology. Our mission is to accelerate the development of life-changing therapies by merging cutting-edge technology with innovative science. We are building a world-class team to drive forward the future of drug discovery. About the Team: We are a mission-driven group of scientists and engineers using cutting-edge computational methods to discover drugs for unmet medical needs. Our work spans machine learning, computational chemistry, biology, and wet lab experimentation , all operating within a high-trust, deeply technical environment. You'll join a team with extremely strong ML talent that is actively pushing the frontier of AI in drug discovery . We are refining how experimental data, biological context, and computational models integrate into a seamless feedback loop. You will help reshape how data flows from experiment → infrastructure → model → decision and increase the speed and scale at which we learn. The Role This is a builder-integrator role inside a deeply technical, cross-domain environment spanning AI/ML, engineering, computational chemistry, biology, and wet lab operations. You will serve as the connective tissue and acceleration engine across these domains. You will work closely with senior leadership to own roadmap definition and execution across critical internal platforms while driving structural improvements in how our teams operate. This role exists to: - Bridge domain silos and reduce friction between ML experimentation and biological context

Software Engineer - Core Infrastructure San Mateo, CA Genesis Therapeutics is building a world-class computational team to solve problems in drug discovery through machine learning, biophysical simulation, and computational chemistry. We are looking for an Infrastructure Engineer that is excited to help develop new medicines and play a critical role in building out our AI platform. You Will - Work on our infrastructure team to maintain and grow our multi-cloud compute infrastructure that supports our ML model training, computational chemistry research, and ongoing drug discovery efforts - Build out our configuration and procedures for monitoring, resource allocation, and deployment automation, as we continue to grow our autoscaling compute clusters to handle larger workloads - Work on orchestration scheduling framework to increase our execution throughput, reliability, and compute utilization across heterogeneous pipelines You Are - 5+ years of experience building and maintaining cloud infrastructure at scale, e.g. within AWS or GCP - Proficient with Python, Bash, Terraform, Ray and Kubernetes - Ideally, experience building and maintaining compute clusters running distributed ML training jobs with 1,000+ GPUs - Nice to have: hands-on experience with physical hardware + datacenter management What We Offer - The opportunity to work on high impact infrastructure that is used to accelerate the discovery of new medicines - A world-class, tight-knit team of good-hearted people across software, machine learning, computational chemistry, medicinal chemistry, and biology - Competitive salary and equity. Medical, dental, and vision insurance, and a 401(k) program About Genesis Molecular AI Genesis Molecular AI is pioneering

CompChem Research Scientist (Free Energy Methods) - Sr. - Principal NYC or SF Bay Area, NYC, or SF Bay Area, California or NY, United States About Genesis Molecular AI Genesis Molecular AI unifies cutting edge molecular machine learning with rigorous physics to discover novel small molecule therapies for severe diseases. Our molecular AI platform, GEMS, combines generative models and high throughput molecular simulation to search chemical space and prioritize compounds with unprecedented speed and accuracy. We are bringing together a world-class computational team to build out the industry's fastest and most accurate small molecule property predictions, by combining the power of machine learning and physics-based methods. About the Team Our computational chemistry team partners with ML researchers, medicinal chemists, and biologists to turn our computational models into real drug candidates for our internal pipeline and our pharma collaborators. You will join a team led by experienced drug hunters and method developers across statistical mechanics, free energy methods, and computer aided drug design. About the Role We are looking for a binding free energy specialist, who is comfortable both with the theory necessary to propose new methodological ideas and with coding necessary to implement them. This individual will advance free energy methods across our platform and own their delivery. You will be the person our teams turn to when they need physics based ranking of tight binders, especially in potency regimes where current models start to flatten out. Your work will directly shape which compounds we make, which ones move forward,

Chief of Staff to the CEO San Mateo, CA Role Summary We are seeking a Chief of Staff to report directly to and support our CEO in key elements of operations and strategy. You'll have direct access to a CEO building at the frontier of AI and drug discovery, at a company with real scale ($300M+ raised, pharma partnerships, an internal pipeline) and real ambition. As a Chief of Staff to the CEO, you'll be at the center of how Genesis operates and where it's going. That means owning the systems that keep the leadership team aligned - quarterly and annual planning, board meeting preparation, exec team facilitation - while also acting as the CEO's trusted voice in internal and external communications. What You'll Do - Provide thought partnership to our leaders. You'll work closely with the CEO and leadership team to drive strategic decisions and contribute to company strategy - Be a force multiplier. You'll take on strategic work directly on behalf of the CEO, owning ad-hoc strategic projects that require pulling together resources and perspectives across the organization - Keep a pulse on the business. You'll meet regularly with teams across the company to surface headwinds, identify inefficiencies, and connect dots that leaders embedded in their functions can't easily see - Drive strategy and operating rhythm. You'll be a thought partner on company strategy and own the systems that keep the leadership team aligned and moving: quarterly and annual planning, OKR setting, exec team meetings, and board meeting

Software Engineer - ML Infrastructure San Mateo, CA, Remote, New York, NY About the Team We're a tight-knit team of proven drug hunters, deep learning researchers, and software engineers united by a common mission - drive AI innovation in biochemistry, discovering and developing groundbreaking therapies for patients suffering from severe disorders. Genesis AI team is focused on developing foundation models for small molecule drug discovery by conducting fundamental research at the intersection of machine learning, physics, and computational chemistry, as well as engineering robust software systems that enable running large scale simulations and training generative and predictive AI models designed to learn from all kinds of molecular data, leveraging our cluster with 1000s of GPUs and 10,000s of CPUs. About the Role We're seeking experienced ML infrastructure engineers to join the team and lead engineering efforts focused on driving forward our ML research agenda for generative modeling of molecular systems, which is instrumental to our mission. As an engineer at Genesis, you will lead rapid iteration on our AI platform and infrastructure, unlocking the next level of performance, efficiency, and scale that was not previously possible. You will build massively distributed training and inference pipelines, core MLOps tools and frameworks, and optimize GPU operations to speed up ML models. Genesis is a highly-collaborative and cross functional environment, and you will work in close partnership with our exceptional engineers, researchers, and scientists. You Will - Lead engineering efforts focused on continuous improvement of the AI platform, focused on rapid build out

ML Research Scientist, Foundation Models (Senior / Staff / Principal) San Mateo, CA, New York, NY 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

ML Research Engineer, Foundation Models (Senior / Staff / Principal) San Mateo, CA, New York, NY ML Research Engineer, 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 unlock new therapies for patients with severe diseases . We conduct fundamental research at the intersection of machine learning, physics, and computational chemistry , pushing the boundaries of each field. The Genesis AI team is building the engine for this revolution. We develop large-scale generative models trained across the full spectrum of molecular data, supported by extensive compute infrastructure and simulation pipelines. The work sits at the intersection of machine learning research, structural biology, and computational chemistry , requiring deep technical rigor and strong interdisciplinary collaboration. About the Role This role is for a highly skilled ML Research Engineer who thrives at the intersection of fundamental research and production-grade engineering . As a core member of the Genesis AI team, you will serve as the engineering pillar for inventing, scaling, and shipping our next generation of foundation models for molecular science . You will partner closely with ML researchers, computational chemists, and drug discovery scientists to translate cutting-edge model ideas into systems that power real drug discovery programs . Your work may involve: - Scaling model pretraining

Fullstack Software Engineer (Senior / Staff) San Mateo, CA, New York, NY Fullstack Software Engineer (Senior / Staff) 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

Applied ML Scientist (Staff / Principal) San Mateo, CA 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. You will work side-by-side with top multidisciplinary researchers to design and build generative foundation models at scale, having access to ample compute and large-scale simulations. About the Role This unique role is for a scientist who is passionate about being a catalyst for applying cutting-edge AI to solve real-world drug discovery challenges. You will be the critical bridge between our long-term research and our experimental drug discovery programs. Your mission is to build, evaluate, monitor, and improve our state-of-the-art models directly into active drug programs, leading the charge on model validation, deployment, and analysis to guide the discovery of new medicines. You will act as both a translator and a strategist, ensuring our research is aimed at the most critical challenges and that our drug hunters can leverage the full power of our industry-leading AI platform. This role requires a deep understanding of cheminformatics, computational chemistry, and experimental techniques, strong data science

AI Scientist/Senior, Clinical & Molecular Genomics Modeling, BRAID South San Francisco, California, United States of America Join our team as a Senior AI Scientist, Clinical & Molecular Genomics Modeling and drive innovation in AI and genomics. Develop advanced models to impact clinical trials, integrate complex biological and molecular data, and collaborate with leading researchers. Shape the future of drug discovery with cutting-edge computational science at Roche.

AI Research Scientist —Generative AI for Materials Discovery Redmond, WA; Pasadena, CA Meta's Reality Labs Research (RL-R) brings together a team of researchers, developers, and engineers to create the future of Mixed Reality (MR), Augmented Reality (AR), and Wearable Artificial Intelligence (AI). The Materials and Systems Innovation (MSI) group within Reality Labs Research creates and accelerates breakthrough materials and device technologies that unblock the path to low-cost, all-day wearable AR devices and advanced sensing and actuating systems for robotics. We identify key technology gaps requiring step-change innovation, build AI-driven autonomous discovery pipelines to compress development timelines, leverage external partners to accelerate research, and deliver high-quality technology solutions through cross-functional, high-performing teams. In this role, you will pioneer the application of generative AI to design novel compounds and molecular crystals, directly accelerating the discovery of next-generation materials for AR/VR devices and advanced robotic systems. Working at the frontier of deep generative modeling, computational chemistry, and agentic AI, you will develop and deploy state-of-the-art models - including diffusion models, flow matching, and transformer-based architectures - that predict and generate stable crystal structures and molecular candidates with target properties. Your work will be tightly integrated into our AI-driven autonomous discovery platform, collaborating with computational chemists and AI agent scientists to close the loop from molecular design to experimental validation. Together, we are going to build advanced prototypes, technologies, and toolsets that can advance how people interact with their surroundings. We invite you to join us as we work to bring these technologies from

Member of the Technical Staff, Molecular Generation New York HQ 🗽 Output has built a biological reasoning model that understands biology at the scale and complexity life actually operates. Our model independently learned the principles of molecular interactions, opening up drug treatments that were previously impossible. We're already generating therapies that traditional approaches cannot reach. The hardest problems in both AI and biology are being solved here, and there is room for you to own one. Output is currently in stealth, operated by a team of repeat founders and biotech veterans with multiple exits in AI x Bio, and backed by top-tier VCs including Y Combinator. You will lead the design and development of Output's generative models, working across molecular modalities to build systems that produce novel, biologically grounded molecules. This role spans the full arc from research to trained model: you design architectures, develop training approaches, run experiments on distributed GPU clusters, and evaluate results. - You will design and build generative architectures for molecular data spanning multiple modalities, including small molecules, peptides, mini proteins and more - You will develop training approaches that learn from diverse biological signal, ensuring the model composes genuinely novel structures - You will build methods for controllable, targeted generation, enabling the model to produce molecules with specified biological properties while satisfying real-world chemical constraints - You will integrate biological reasoning from our foundation model into the generative pipeline, using learned biological representations to guide and condition generation - You will own training end-to-end:

Bioengineer / Molecular Biologist Lausanne | OnSite Adaptyv is building an automated lab thats let AI agents run biology experiments. We're entering the era of agentic science where AI models can now design novel proteins, propose hypotheses, and iterate on experimental results. But they can't run the experiments themselves - that's still a manual, months-long process. We're building the infrastructure that gives AI agents access to the physical world. We are one of the fastest growing biotech companies, trusted by leading biopharmas, frontier AI labs, and the techbio companies pushing the field forward. This is a rare chance to help advance some of the most important work happening in biotech today. Our automated lab is powered by a deep software + hardware stack: lab instruments worth millions of USD reverse-engineered into API-controllable hardware, dozens of devices orchestrated through complex workflows, full observability on everything that happens in the lab, processing pipelines for messy physical-world data, and AI systems that troubleshoot production results and accelerate assay development. We're growing rapidly and are hiring for talented people to scale and support the massive demand for AI-driven wet lab experimentation. ABOUT THE ROLE This is a hands-on research role in our biology and production team. You'll work on the science that underpins everything Adaptyv does: developing and optimizing protein expression systems, running molecular biology workflows, and pushing the boundaries of what we can produce and characterize at scale. We express proteins at high volume across cell-free and cell-based systems, run DNA synthesis and

Founders Associate Lausanne | OnSite Adaptyv is building an automated lab thats let AI agents run biology experiments. We're entering the era of agentic science where AI models can now design novel proteins, propose hypotheses, and iterate on experimental results. But they can't run the experiments themselves - that's still a manual, months-long process. We're building the infrastructure that gives AI agents access to the physical world. We are one of the fastest growing biotech companies, trusted by leading biopharmas, frontier AI labs, and the techbio companies pushing the field forward. This is a rare chance to help advance some of the most important work happening in biotech today. Our automated lab is powered by a deep software + hardware stack: lab instruments worth millions of USD reverse-engineered into API-controllable hardware, dozens of devices orchestrated through complex workflows, full observability on everything that happens in the lab, processing pipelines for messy physical-world data, and AI systems that troubleshoot production results and accelerate assay development. We're growing rapidly and are hiring for talented people to scale and support the massive demand for AI-driven wet lab experimentation. ABOUT THE ROLE Adaptyv is growing fast. We are significantly expanding our lab this year, onboarding more and more customers every week, and building the systems needed to keep the company running smoothly as we scale. We are looking for a Founders Associate to own and build the operational backbone of the company as we scale. This is a high-ownership generalist role: you'll take entire

Genesys Architect Developer Bengaluru, Karnātaka, India Embrace the role of a Genesys Architect Developer and drive the future of enterprise contact center solutions. Leverage your expertise in Genesys Cloud, routing strategies, and customer engagement to build scalable, innovative platforms. Collaborate with cross-functional teams and shape the next generation of digital customer experiences at a global ecommerce leader.

Registered Nurse - Inpatient Dialysis RN 01255 - Genesys Acute posted: Posted 30+ Days Ago

Senior Architect (CCaaS, Genesys Cloud) Prague, Praha, hlavní město, Czech Republic Your IT Future, Delivered. Senior Architect (CCaaS, Genesys Cloud). With a global team of 5600+ IT professionals, DHL IT Services connects people and keeps the global economy running by continuousl...

Foundation and generative models for biomolecules Berlin, Germany or Palo Alto, CA or Zurich, Switzerland At Inceptive, you will drive forward development that could help billions of people. To accomplish this, you will be part of a collaborative, antedisciplinary team building our biological software. The design space of biomolecules is unimaginably vast - far beyond what can be explored experimentally. Yet within this space lie molecules with properties essential for new medicines. Our machine learning models learn to design therapeutic biomolecules with specific, desirable functions. We advance the state of the art in molecular design by training large-scale foundation models and developing cutting edge generative approaches. The models learn from diverse heterogeneous datasets and are refined through focused fine-tuning and feedback from experiments. Key to progress is a team that combines exceptional machine learning expertise with thorough domain understanding. You will collaborate closely with other machine learning researchers and engineers, as well as computational and experimental biologists, to advance these models and translate their capabilities into real therapeutic designs. Your Mission, should you choose to accept it - Embody our vision of an antedisciplinary environment and embrace learning about areas outside of your traditional area of expertise - Develop, implement, train, and iteratively improve state-of-the-art models for biomolecule design - Analyze, visualize, and communicate results to support team efforts in improving models and data - Create, deploy, and refine tools for efficient, reliable machine learning experimentation and production - Work with biologists to collect data for the training and evaluation

Data Scientist, Lab & Protein Data Lausanne | OnSite Adaptyv is building an automated lab thats let AI agents run biology experiments. We're entering the era of agentic science where AI models can now design novel proteins, propose hypotheses, and iterate on experimental results. But they can't run the experiments themselves - that's still a manual, months-long process. We're building the infrastructure that gives AI agents access to the physical world. We are one of the fastest growing biotech companies, trusted by leading biopharmas, frontier AI labs, and the techbio companies pushing the field forward. This is a rare chance to help advance some of the most important work happening in biotech today. Our automated lab is powered by a deep software + hardware stack: lab instruments worth millions of USD reverse-engineered into API-controllable hardware, dozens of devices orchestrated through complex workflows, full observability on everything that happens in the lab, processing pipelines for messy physical-world data, and AI systems that troubleshoot production results and accelerate assay development. We're growing rapidly and are hiring for talented people to scale and support the massive demand for AI-driven wet lab experimentation. ABOUT THE ROLE You'll build out the data science layer of Adaptyv's foundry - the work that turns tens of thousands of raw, messy experimental readouts into clean, trustworthy, structured data that our customers, our models, and our own scientists can rely on. Binding (BLI/SPR), developability, biophysical, and functional assays all produce data at scale; your job is to make that

Member of the Technical Staff, Cheminformatics New York HQ 🗽 | Remote The Role Output has built a biological reasoning model that understands biology at the scale and complexity life actually operates. Our model independently learned the principles of molecular interactions, opening up drug treatments that were previously impossible. We're already generating therapies that traditional approaches cannot reach. The hardest problems in both AI and biology are being solved here, and there is room for you to own one. Output is currently in stealth, operated by a team of repeat founders and biotech veterans with multiple exits in AI x Bio, and backed by top-tier VCs including Y Combinator. You accelerate the path from a generated molecule to a synthesized compound. This role continues to build the models and computational methods that optimize Output's molecular generation for practical chemistry. - You will continue developing and training models that incorporate knowledge of chemical synthesis routes and reactions, steering molecular generation toward molecules that are efficient to synthesize - You will build scalable computational tools and methods that evaluate synthetic feasibility across generated molecular libraries, systematically and at scale - You will interpret model inputs and outputs in chemistry terms, translating between the language of generative AI and the language of synthesis - You will work with the drug discovery and model teams, bringing chemistry expertise to molecular evaluation and candidate prioritization - You will build and maintain cheminformatics pipelines for molecular analysis, property calculation, and candidate assessment About You You have

Member of the Technical Staff, Biological Data New York HQ 🗽 | Remote The Role Output has built a biological reasoning model that understands biology at the scale and complexity life actually operates. Our model independently learned the principles of molecular interactions, opening up drug treatments that were previously impossible. We're already generating therapies that traditional approaches cannot reach. The hardest problems in both AI and biology are being solved here, and there is room for you to own one. Output is currently in stealth, operated by a team of repeat founders and biotech veterans with multiple exits in AI x Bio, and backed by top-tier VCs including Y Combinator. You will own the data that our models learn from. This role requires a deep understanding of molecular biology - what a biological data source contains, what it implies, and what is missing. The quality and coverage of training data determines what our models can learn, and the biological insight behind how that data is constructed is the difference between a model that memorizes and one that reasons. - You will construct training datasets that capture how proteins and molecules interact, drawing from diverse biological data sources and extending them with your understanding of molecular principles - You will develop methods to expand training data beyond what exists in public databases, using biological and chemical reasoning to create new training signal where current data is sparse or absent - You will design benchmarks grounded in real molecular phenomena, measuring whether