L

Latent Labs

Develops foundational AI for molecular biology

Computational Protein Designer

Full-Time
No salary listed
Mid
PhD
San Francisco, CA, USA
Hybrid
Biology & BiotechQuantitative Biology & Biostatistics

About the job

Requirements
  • A proven track record of running protein design campaigns end-to-end and leveraging computational tools and knowledge of biochemistry or structural biology to design proteins for functional requirements and synthetic biology applications.
  • Experience with generative modeling, including model training and large-scale inference.
  • A PhD or equivalent industry experience in computational biology, bioinformatics, computer science, biochemistry, structural biology, physics, biophysics, bioengineering, chemical engineering, or a related field.
  • Research experience in protein biochemistry using computational expertise.
  • Extensive wet-lab biology experience and the ability to independently execute end-to-end design campaigns, including experimental validation.
  • A proven track record of delivering successful commercial or academic research projects, demonstrated through publications, patents, or commercially impactful outcomes.
  • Excellent communication and presentation skills, including the ability to convey complex scientific concepts to technical and non-technical audiences.
  • Passion for making a positive impact and flexibility in adapting to different approaches and methodologies.
  • Ability to work efficiently in a fast-paced and ambiguous environment and optimize processes for speed and repeatability.
  • Advocacy for laboratory automation through hardware and software.
Responsibilities
  • Analyze protein design problems based on functional requirements, biochemistry, structural biology, and sequence homology.
  • Generate proteins using proprietary generative artificial intelligence models and optimize designs for experimental validation.
  • Coordinate with lab-based protein engineers to plan and optimize the design process and validation strategy.
  • Analyze and leverage experimental results to improve subsequent designs and increase success across validation rounds.
  • Collaborate with machine learning scientists to fine-tune and prompt generative artificial intelligence models.
  • Develop and carry out experimental validation strategies for computationally designed proteins, including protein expression and purification, biophysical characterization, and functional assays.
  • Act as an interface between machine learning model development and experimental validation.
  • Capture bioengineering learnings and feedback for the machine learning unit, and provide corresponding feedback to experimental teams.
  • Foster collaboration and create clarity and alignment between different organizational units.
  • Improve the use, serving, and integration of artificial intelligence models by providing feedback to software engineers and the foundational machine learning unit.
  • Improve data management systems and workflows.
  • Maintain publication-grade scientific standards and stay current with developments in synthetic biology.
  • Continue building knowledge of generative artificial intelligence and protein and cell biology.
  • Organize and present at internal reading groups and attend and present at relevant conferences.
Desired Qualifications
  • Experience leveraging generative artificial intelligence or other machine learning models in synthetic biology applications.
  • Experience with homology-based and structural bioinformatics and answering scientific questions using very large databases.
  • Experience working in startups and helping a young biotechnology company grow.

About the company

Latent Labs builds foundational biology models that power generative AI for biology. It offers AI tools to help researchers design new antibodies, optimize existing enzymes, and advance genetic engineering. The models translate biological data into actionable designs and optimization suggestions for lab use, provided through collaboration with partners. The goal is to accelerate molecular biology by giving researchers AI-guided design and directions for experiments.

Company Size

11-50

Company Stage

Series A

Total Funding

$59.1M

Headquarters

London, United Kingdom

Founded

2023

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Simplify's Take

What believers are saying

  • GenScript validated Latent-X2 in January 2026, strengthening wet-lab trust and adoption.
  • Latent-Y showed confirmed nanobody binders on six of nine targets, with single-digit nanomolar affinity.
  • AWS and NVIDIA partnerships in 2026 expand compute, distribution, and enterprise reach.

What critics are saying

  • Latent Labs had only about 20 employees in March 2026, limiting execution capacity.
  • Free access launched July 15, 2026, risking weak monetization before competitors copy features.
  • Existential risk: failed partner conversions after GenScript validation would collapse biotech credibility.

What makes Latent Labs unique

  • March 2026 Latent-Y autonomously designs antibodies from prompts, not manual workflows.
  • Latent-X2 plus Latent-Y integrates epitope selection, candidate generation, and validation end-to-end.
  • NVIDIA Blackwell and Nebius delivered over 4x training speedups and 60% faster inference.

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Benefits

Health Insurance

Parental Leave

Hybrid Work Options

Growth & Insights and Company News

Headcount

6 month growth

36%

1 year growth

36%

2 year growth

52%
Business Wire
Mar 23rd, 2026
Latent-Y AI agent designs therapeutic antibodies in hours, 56x faster than expert teams

Latent Labs has launched Latent-Y, an AI agent that autonomously designs therapeutic antibodies from text prompts, reducing weeks of expert work to hours. The system is powered by Latent-X2, the company's frontier model for drug-like antibody and peptide design. Latent-Y operates independently, analysing target molecules, identifying viable epitopes, designing antibody candidates and validating them computationally. Scientists can run the agent fully autonomously or pause at each stage for review. The London and San Francisco-based company has demonstrated lab-validated results across three antibody design campaigns, including epitope discovery yielding nanomolar-affinity binders. User studies showed PhD-level experts completed design campaigns 56 times faster using Latent-Y compared to independent expert estimates. The platform is now available to selected partners through the Latent Labs platform.

PR Newswire
Jan 28th, 2026
GenScript partners with Latent Labs as wet-lab validator for AI drug discovery model Latent-X2

GenScript Biotech Corporation has announced its role as wet-lab partner for Latent Labs' Latent-X2, a next-generation AI model that designs antibodies and peptides with drug-like properties. GenScript provides high-throughput expression, purification and functional testing of AI-generated molecules, enabling rapid iteration between computational predictions and biological performance. Using its TurboCHO™ High Throughput Platform and cell-free expression systems, GenScript screens AI-designed antibodies, minibinders and peptides to compare candidates and collect data on developability and binding. This reduces reliance on iterative wet-lab optimisation. The collaboration addresses a key industry challenge by accelerating timelines whilst improving likelihood of clinical success. Founded in 2002, GenScript supports over 200,000 customers across 100-plus countries with a team of 5,500-plus employees.

Wow Partners, Inc.
Feb 13th, 2025
Latent Labs raises $50M for AI biology

Latent Labs, an AI-based biology platform developer, has emerged from stealth mode, securing $50 million in funding. The round was co-led by Radical Ventures and Sofinnova Partners, with participation from Flying Fish, Isomer, 8VC, Kindred Capital, and Pillar VC. Notable angel investors include Jeff Dean, Aidan Gomez, and Mati Staniszewski. Founded by Simon Kohl, a key figure in the Nobel Prize-winning AlphaFold2 project, Latent Labs aims to revolutionize drug development with generative AI technology.

TechCrunch
Feb 13th, 2025
Founded by DeepMind alumnus, Latent Labs launches with $50M to make biology programmable | TechCrunch

A new startup from one of the key scientists at Google DeepMind exits stealth today with $50 million in funding.

Business Insider
Aug 8th, 2023
DeepMind's secret mafia: Meet the stealth startups emerging from Google's AI lab

Alphabet's AI research lab DeepMind nurtures the industry's top talent. It's also spawned a wave of secretive new startups.