Head of Lab Platform
Latent LabsSan FranciscoPosted 30 March 2026
Tech Stack
Job Description
Head of Lab Platform
THE OPPORTUNITY
We are seeking a Head of Lab Platform to join our team working at the interface of generative AI and synthetic biology. You will lead and evolve our experimental capabilities, connecting high throughput assay work with our AI workflows and driving us towards a fully autonomous lab. This is an opportunity to think big: to build the infrastructure that closes the loop between biological experimentation and machine learning at scale. You will oversee a team of scientists, set the strategic vision for our lab platform, and work in close collaboration with machine learning teams. A strong blend of software, hardware, and biomolecular skills is essential.
Who we are
At Latent Labs, we are building frontier models that learn the fundamentals of biology. We pursue ambitious goals with curiosity and are committed to scientific excellence. Before building Latent Labs, our team co-developed DeepMind’s Nobel-prize winning AlphaFold, invented latent diffusion, and built pioneering lab data management systems as well as high throughput protein screening platforms. At Latent Labs you will be working with some of the brightest minds in generative AI and biology.
Our team is committed to interdisciplinary exchange, continuous learning and collaboration. We’re looking for innovators passionate about tackling complex challenges and maximizing positive global impact.
Who you are
- You are a lab automation expert. You bring a rare blend of hardware and software lab skills. You have deep experience designing, deploying, and troubleshooting automated workflows, liquid handling systems, and efficiently integrating with LIMS infrastructure. You think creatively about how to connect wet lab operations with agentic AI workflows, and you have concrete ideas for how to push our platform towards full lab autonomy.
- You are a strong biomolecular and biochemistry scientist. You have generalisable expertise across a range of assay types and biological modalities. You are deeply familiar with workflows involving DNA synthesis, assembly, cloning, transformation, and quantitative read-outs (e.g. flow cytometry, NGS, binding affinity assays). You can scale these workflows into the high throughput regime and have hands-on experience with both arrayed and pooled formats. You thrive at the interface of wet lab and data, understanding how experimental design choices shape what can and cannot be learned from the data collected.
- You are a successful scientist. You have a Ph.D. or equivalent experience in biology, synthetic biology, computational biology, or a related field. You have a proven track record of leading successful commercial and / or academic research projects, demonstrated through publications and contributions to the scientific community, e.g. in Nature, Science, Cell or PNAS.
- You empower your team. You lead teams of scientists. You win over and motivate people with great ideas, appreciation and empathy. You love to connect people and enable them to perform at their highest levels. You have excellent communication and presentation skills with the ability to convey complex scientific concepts to both technical and non-technical audiences.
- You are a mission driven innovator. You are passionate about making a positive impact on the world, whether it's for patients, partners or beyond. You are motivated by the end goal and are flexible in adapting to different approaches and methodologies. You constantly seek new, innovative ways to engineer biology while leveraging existing knowledge and expertise.
- You thrive in a dynamic and ambiguous environment. You excel in a fast-paced setting where goals must be achieved efficiently and urgently. You have a keen eye for creating then optimising processes to improve speed and repeatability. You are a champion for lab automation — across hardware, software, and the agentic workflows that will increasingly orchestrate both. You are excited about what a fully autono ... (truncated, view full listing at source)
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