About the job
Job Summary
Iambic Therapeutics is on the lookout for an innovative Machine Learning Scientist to join our team and focus on cutting-edge transformer-based diffusion techniques aimed at predicting biomolecular structures. In this pivotal role, you will pioneer the development of generative models that utilize tokenized representations of structures, significantly contributing to our advanced machine learning technologies, including NeuralPLexer and Enchant.
Your work will merge generative modeling, structural biology, and representation learning. You will craft and train structure tokenizers, build diffusion models over learned token spaces, and curate extensive biomolecular datasets, benchmarking model performance against state-of-the-art methodologies—all with the goal of accelerating drug discovery.
We are open to hiring across various levels (RS I, RS II, and Senior) and encourage applications from candidates ranging from recent PhD graduates to seasoned researchers with a robust publication record or deployment experience.
Key Responsibilities
Design, implement, and train both discrete and continuous diffusion models for biomolecular structure predictions.
Develop and refine structure tokenizers, focusing on vector-quantized representations for 3D molecular and protein structures.
Create and maintain data processing pipelines for large-scale biomolecular structure datasets.
Train models across multi-GPU clusters, overseeing large-scale training initiatives.
Establish comprehensive benchmarking and evaluation workflows; validate against external benchmarks while focusing on internal discovery-related metrics.
Collaborate with ML scientists and computational chemists to integrate models into drug discovery workflows.
Present findings to internal teams, external partners, and at scientific conferences.
Provide mentorship to interns and junior team members through code reviews and technical guidance (Senior level).
Qualifications
Required
PhD in Machine Learning, Computer Science, Computational Chemistry, Physics, or a related computational STEM field, or equivalent industry experience.