Machine Learning Scientist, Pretraining

About the role

Profluent, an AI lab focused on biology, is seeking a motivated Machine Learning Scientist to lead research on pretraining large‑scale deep learning models for biomolecular design. You will work at the intersection of generative modeling, language processing, and protein engineering, rapidly prototyping and evaluating new algorithms in the biomolecular domain.

Key responsibilities

• Design and develop state‑of‑the‑art autoregressive, diffusion, and representation learning models for protein design.
• Collaborate with machine learning and protein design teams to adapt pretraining techniques from other domains to biomolecular deep learning models.
• Architect, implement, and optimise core infrastructure supporting the pretraining of protein language models.
• Curate relevant datasets and create evaluation tasks for rigorous assessment of generative models.
• Implement, analyse, and interpret computational approaches and present results in regular update meetings.
• Contribute to the scientific and strategic vision of the company within a fast‑paced, interdisciplinary team.

Required profile

• PhD (or equivalent industry experience) in Computer Science, Machine Learning, NLP, Applied Math, Computational Biology, Statistics, or a related field.
• Proven experience conceiving, implementing, and evaluating novel machine learning and pretraining large‑scale models in the biomolecular domain.
• Publications at top machine learning conferences (NeurIPS, ICML, ICLR) or scientific journals (Nature, Science, etc.) or experience pre‑training LLMs at frontier AI/ML labs.

Required skills

• Proficiency with modern deep learning frameworks such as PyTorch or JAX.
• Experience with cloud compute platforms (GCP, AWS, Azure, OCI).
• Ability to curate bioinformatics datasets and design rigorous evaluation tasks.