Careers

Build the systems that let biology learn faster.

We are hiring scientists and engineers to connect large-scale protein experiments with the next generation of machine learning and protein design.

Machine Learning · Full time

Machine Learning Scientist, Biological Foundation Models

We are looking for someone who wants to build new machine-learning architectures from first principles around biological sequence and experimental data. This is not a role for wrapping existing language models around a protein database. You will work directly with large, internally generated datasets linking sequence to expression, binding, stability and other measured phenotypes, and develop models that can learn from the structure of those experiments.

What you will do

  • Design and implement new neural architectures for protein sequence, experimental measurements and iterative design data.
  • Build models that learn jointly from sequence, assay context, measurement uncertainty and repeated experimental rounds.
  • Develop active-learning and experiment-selection strategies for directed evolution and high-throughput protein optimization.
  • Work directly with wet-lab scientists to determine what data should be generated next, not just how existing data should be modeled.
  • Establish rigorous evaluation methods for generalization across proteins, targets, assays and experimental campaigns.

What we are looking for

  • Deep experience developing modern machine-learning models in PyTorch, JAX or an equivalent framework.
  • Strong grounding in representation learning, generative modeling, transformers, diffusion, graph methods or related architectures.
  • Comfort building models from scratch rather than relying exclusively on pretrained APIs.
  • Experience with biological sequence data is valuable, but exceptional ML researchers from adjacent fields are encouraged to apply.
Apply by email
Protein Design · Full time

AI Protein Design Scientist, Vaccines & VLPs

We are looking for a computational protein scientist to design proteins that can be built and tested rapidly in our cell-free systems, with a particular focus on vaccine antigens, virus-like particles and programmable protein assemblies. You will work across computational design and experimental validation, using real wet-lab feedback to improve each successive round of design.

What you will do

  • Design and rank vaccine antigens, VLP components and engineered protein assemblies using modern protein-design methods.
  • Apply structure prediction, sequence design, generative models and physics-informed approaches where each is most useful.
  • Work with experimental scientists to translate designs directly into cell-free expression and functional testing.
  • Analyze expression, assembly, stability and functional data to determine why designs succeed or fail.
  • Build iterative computational-experimental workflows in which each experimental round informs the next design round.

What we are looking for

  • Experience in computational protein design, structural biology, protein engineering or a closely related field.
  • Hands-on familiarity with current protein-design and structure-prediction tools.
  • Strong Python skills and comfort working with sequence, structural and experimental datasets.
  • Experience with viral proteins, capsids, vaccine antigens, self-assembling proteins or VLPs is particularly valuable.
Apply by email

Interested in joining Liberum?

Send us a CV, a short note about what you have built, and links to work you think we should see.