Machine Learning Researcher

My client is a well-funded, frontier-stage organization developing Physical AI for molecules, integrating deep learning with molecular and atomistic modeling.

This is a chance to join a world-class team of ML researchers, engineers, and scientists working at massive scale in compute, data, and ambition. The environment suits those who thrive in fast moving, high-impact research settings.

We're seeking an ML Research Scientist passionate about representation learning and molecular modeling to help develop next generation foundation models for molecular AI.

You'll work at the intersection of model architecture, training strategy, and physical reasoning
, creating systems that push the limits of molecular understanding.

• Designing and implementing advanced representation models (e.g., GNNs, geometric transformers) for molecular and atomistic systems.
• Developing pre, mid, and post training pipelines to optimize foundation model performance.
• Applying reinforcement or self supervised learning strategies to maximize data efficiency.
• Collaborating with physicists and chemists to ensure ML models align with physical principles.
• Prototyping, benchmarking, and scaling new architectures across the internal research ecosystem.

You bring both technical excellence and scientific curiosity, with experience bridging ML theory and physical application domains.

• PhD or equivalent experience in Computer Science, Machine Learning, Physics, Chemistry, or related field.
• Proven experience running ML research at scale, from data handling to training and validation.
• Strong understanding of 3D geometric deep learning or representation learning methods
  .
• Proficiency in Python and frameworks such as Py Torch or JAX
  .
• Ability to communicate and collaborate across interdisciplinary teams.

• Experience with self supervised or generative modeling approaches.
• Familiarity with equivariant GNNs (NequIP, MACE, Sch Net, PaiNN, etc.).
• Background in computational chemistry
  , materials science
  , or biophysics
  .
• Experience working on distributed compute or multi site ML research projects.

You're a Machine Learning Researcher ready to work on frontier problems in molecular AI, I'd love to speak with you.