Output Biosciences jobs

Head of Biology New York HQ 🗽 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 own the feedback loop between Output's models and the lab. You go deep into specific biological problems, translate what the biology requires into priorities for data and modeling, and manage through CRO partners the experimental cycle that validates model outputs and generates new data. - You will own the active learning cycle between Output's models and experimental validation: designing experiments, managing CRO partners for synthesis and testing, interpreting results, and feeding them back to improve the models - You will dive into specific biological problem areas, developing the expertise needed to translate nuanced biological requirements into priorities for data construction, modeling, and evaluation - You will manage CRO relationships for peptide and molecular synthesis, biological assays, and experimental testing, designing each campaign to generate maximally informative data - You will collaborate with the engineering team to design and build biology-specific agent skills and workflows, encoding

Head of Discovery 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 are a drug hunter. You own the scientific strategy behind Output's drug discovery programs. You help select targets for our pipeline, evaluate what the models generate, and make the scientific decisions that advance candidates from computational generation to real-world testing. - You will identify and evaluate therapeutic targets, building the scientific rationale for which programs to pursue and why - You will analyze model outputs to assess drug candidates, evaluating biological plausibility, therapeutic potential, and readiness for advancement - You will prioritize candidates and make scientific go/no-go decisions, advancing the strongest compounds through the discovery pipeline - You will manage CRO partnerships for candidate synthesis and biological testing, designing experiments that validate or refine drug design hypotheses - You will work closely with the founders and model team, bringing drug discovery expertise to model evaluation and development priorities - You will stay current

Software Engineer, Agents New York HQ 🗽 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 build the agent infrastructure that turns model capabilities into usable tools and workflows. This role owns the orchestration layer, the inference serving, the internal tooling, and the interfaces that researchers and external systems interact with. - You will design and build the agent orchestration system that composes model capabilities into multi-step workflows, handling sequencing, state management, and error recovery - You will implement agent skills and tools that expose model capabilities to automated and interactive workflows - You will build inference infrastructure for serving models efficiently, optimizing for latency, throughput, and reliability - You will design and build APIs and integrations, including MCP-compatible interfaces, that allow external systems and users to interact with Output's models - You will build internal tools that accelerate the research team's work, from experiment management to evaluation pipelines - You will establish and maintain software engineering practices across the

Research Intern (PhD), Machine Learning New York HQ 🗽 | Bay Area 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. Our internships offer flexible commitment, with a minimum of 20 hours per week, ranging 12 to 24 weeks. We have various start dates available to accommodate your academic schedule. There may be opportunities for full-time employment upon successful completion of your PhD. The Role You will own a research project that directly advances Output's research and its path to new therapies. This is not a side project: your work will contribute to the same models and methods the full-time team builds on. We will select a project together based on your research interests and our priorities, with a path to publishing your work at top-tier venues and the opportunity to continue with additional projects throughout the year. About You - You are currently pursuing a PhD in machine learning, computer science, computational biology, physics, mathematics, or a related field - You have a

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:

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

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, Pretraining 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 advance the core architecture and training of Output's foundation model, the system that learns biological reasoning from data. This role spans the full arc from research to trained model: you design architectures, develop training objectives, run pretraining at scale, and evaluate what the model has learned. - You will push forward the architecture and training objectives of our foundation model, designing approaches that are purpose-built for biological reasoning - You will develop methods for the model to learn across multiple biological data modalities simultaneously, building unified representations of molecular biology - You will extend the model's reasoning capabilities across biological phenomena, pushing what it can predict and understand about binding, molecular properties, and biological function - You will own pretraining end-to-end: experiment design, distributed training on multi-GPU clusters, hyperparameter optimization, and iteration - You will design evaluation frameworks that measure whether the model

Member of the Technical Staff, Interpretability 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 continue developing methods to understand what our foundation model learns about biology, and build the tools that make it a glass box model. We believe that in biology, a model's reasoning must be visible. And the features you find are not just explanations: they expand what the model can do. - You will continue developing our methods for probing and reverse-engineering the model's learned representations, understanding how it encodes biological information across molecular scales - You will design and run experiments to identify and characterize capabilities, mapping what the model has learned about molecular interactions and biological function - You will build methods to extract the model's biological understanding as explicit, usable outputs that downstream systems and researchers can act on - You will create tools that connect model internals to meaningful biological concepts, making the model's reasoning interpretable to scientists and useful

Account Manager - Biosciences Remote, Belgium Embrace the role of an Account Manager - Biosciences and drive growth by promoting innovative life science solutions across Belgium. Leverage your sales expertise and scientific background to build strong customer relationships, manage accounts, and contribute to impactful scientific discovery. Shape the future of biosciences with Thermo Fisher Scientific.

Account Manager (Bioscience Division) Singapore, Singapore Embrace the opportunity to become an Account Manager in the Bioscience Division at Thermo Fisher Scientific. Drive revenue growth, build strategic customer relationships, and promote innovative scientific solutions. If you have a background in life sciences or laboratory sales and excel at territory management, this is your chance to make a global impact.

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