Applied Research Engineer - Post-Training

About the role

Helical is looking for an Applied Research Engineer – Post‑Training to lead the end‑to‑end post‑training workflow for biological foundation models. You will turn general‑purpose models into therapeutic‑specific tools that pharma and biotech customers can use to accelerate target identification and hit discovery.

Key responsibilities

• Design, implement and operate post‑training pipelines that align foundation models to therapeutic contexts and client use cases.
• Build validation frameworks that link model improvements to biological ground‑truth data, including embeddings and perturbation datasets.
• Run experiments from hypothesis generation through distributed GPU training, analysis and delivery to customers.
• Collaborate with ML infrastructure engineers and biologists to ensure scientific relevance of outputs.
• Contribute to Helical’s open‑source tooling (helical‑package) and guide the technical direction of post‑training capabilities.

Required profile

• MSc or PhD in Machine Learning, Computational Biology or a related discipline, or equivalent industry experience.
• Hands‑on experience with post‑training techniques such as fine‑tuning, LoRA, DPO, RLHF, or similar.

Required skills

• Fine‑tuning, LoRA, DPO, RLHF.
• Working with embeddings and perturbation data.
• Use of external resources such as OpenTargets.
• Distributed GPU training infrastructure.
• Open‑source tooling development (helical‑package).