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San Francisco, California, United States
Onsite
For decades, drug discovery has relied on screening millions of molecules and hoping one works. Latent Labs is building the engineering alternative: frontier AI models that design medicines computationally, directly from first principles.
Since founding in 2023, we've released four products already accelerating research from pain relief to cancer therapy, most recently Latent-Y, the first lab-validated agent for drug design. Several of our team led foundational work behind Google DeepMind's AlphaFold, so we’re working at that level of research and beyond, backed by Radical Ventures and Sofinnova Partners.
We are seeking hands-on Scientists and a Sr. Scientist to join our team at the interface of generative AI and biology. Our models design novel proteins, and our experimental team develops and runs assays to characterize their properties and functions, identify strengths and failure modes, and guide subsequent model development.
For both roles, you will develop and execute high-throughput assays, drawing on a strong foundation in molecular biology, mammalian cell culture, and experimental design. We are looking for an adaptable scientist who selects methods based on the scientific question, brings depth in at least one relevant technical area, and enjoys learning new approaches. You will work closely with other experimental scientists, ML researchers, automation colleagues, and technical expert consultants to establish reliable workflows and generate high-quality, interpretable data.
For the Sr. Scientist role, on top of the scientist requirements, qualified applicants will have experience mentoring others in professional and technical context; additional years of industry experience; and experience managing complex projects with CROs, with full ownership including understanding SOWs, negotiating contracts, and troubleshooting.
Develop and run assays. Independently design, execute, optimize, and troubleshoot cell-based and biochemical assays to evaluate model-generated proteins, with an emphasis on high-throughput plate-based workflows.
Establish new experimental capabilities. Work with technical expert consultants to select and implement new assays, interpret unfamiliar data, and translate specialist knowledge into reproducible internal workflows.
Improve screening workflows. Collaborate with the automation team to increase throughput, reproducibility, and efficiency, and contribute to the development of our screening platform.
Analyze and interpret results. Use Python to process experimental data, assess assay quality, and communicate findings and limitations. Establish appropriate controls and QC criteria. Document methods, samples, experimental conditions, and analysis results using Benchling, a LIMS, or similar tools.
Connect experiments to model development. Work with ML colleagues to provide well-documented data and biological context, and help translate results into actionable insights for subsequent design cycles.
You have a strong scientific foundation. You hold a PhD in molecular biology, cell biology, biochemistry, or a related field, with at least 1-3 years of relevant industry research experience for Scientist; >3 years for Sr. Scientist. You can take an assay from initial feasibility testing through optimization and reproducible execution.
You have experience with high-throughput workflows. You have developed or run high-throughput experiments, ideally using plate-based assays and laboratory automation. You understand how experimental design, controls, and sample handling affect data quality.
You bring practical molecular and cellular biology skills. You have experience in molecular biology and mammalian cell culture, alongside relevant methods such as molecular cloning, cell-based functional assays, flow cytometry/FACS, ELISA, or next-generation sequencing. You do not need experience with every technique listed.
You are comfortable with large scale experimental data. You are proficient in Python and Jupyter notebooks for data processing, analysis, and visualization, and can produce clear, reproducible analyses. You maintain accurate experimental records and have experience using Benchling, a LIMS, or comparable tools to track samples and associated data.
Relevant Technical Expertise. We are looking for depth in at least one of the areas below, together with the ability and interest to learn adjacent methods. We do not expect expertise across all three.
Gene Editing and Protein–DNA Interaction Characterization
Experience developing biochemical and/or cell-based assays to characterize gene-editing technologies or protein–DNA interactions. Relevant experience may include measuring on-target editing efficiency, assessing off-target activity, or characterizing DNA-binding affinity and specificity.
Membrane Protein Characterization
Experience developing functional assays for membrane proteins, such as ion channels or solute carrier transporters. Relevant methods may include FLIPR assays, thallium flux, voltage-sensitive dyes, transporter activity assays, or manual or automated patch-clamp electrophysiology.
Protein Biochemistry and Biologics Characterization
Experience expressing and characterizing proteins using cell-free, mammalian, or other relevant expression systems. Relevant expertise may include binding affinity, biochemical activity, stability, or developability characterization across one or more protein formats, such as peptides, macrocycles, antibodies, or enzymes.
Experience in an early-stage biotech, including establishing new assays, workflows, or laboratory processes.
Experience transferring consultant-developed or externally developed assays into an internal lab.
Experience improving automated screening workflows or sample and data management systems.
Familiarity with Git and GitHub for version control and collaborative analysis.
Experience working with computational scientists or evaluating computationally designed proteins.
The opportunity to work at the frontier of AI and computational biology, alongside a team that has already delivered Nobel Prize–caliber science, on a mission to transform biology into an engineering discipline.
We hold every contribution, computational or experimental, to the same exacting bar, and push the boundaries to deliver at exceptional pace. Beyond our competitive compensation, equity and benefits, we are expanding rapidly so there are many opportunities for significant ownership and impact across all roles.
