Machine Learning Scientist
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Job Description
Machine Learning Scientist developing generative models for biomolecular structure prediction at Iambic Therapeutics. Contributing to core ML technologies relevant for drug discovery.
Responsibilities:
- Design, implement, and train discrete and continuous diffusion models for predicting biomolecular structure tokens
- Develop and iterate on structure tokenizers, including vector-quantized representations of 3D molecular and protein structure
- Build and maintain data processing pipelines for large-scale biomolecular structure datasets
- Train models on multi-GPU clusters, managing large-scale training runs
- Develop rigorous benchmarking and evaluation workflows; validate against external benchmarks while prioritizing internal discovery-relevant metrics
- Collaborate with ML scientists, computational chemists, and drug discovery teams to integrate models into discovery workflows
- Communicate results to internal teams, external partners, and at scientific conferences
- Mentor interns and junior team members through code reviews, technical guidance, and best practices (Senior level)
Requirements:
- PhD in machine learning, computer science, computational chemistry, physics, or related computational STEM field, or equivalent industry experience demonstrating comparable depth
- Strong Python and PyTorch skills, including end-to-end implementation and training of deep learning models
- Demonstrated experience in one or more of the following:
- 3D atomistic or molecular modeling
- Vector quantization and learned discrete representations
- Diffusion, flow-matching, or related generative modeling in continuous vector spaces
- Strong engineering practices: reproducible experimentation, clean code, testing, and performance-aware debugging
- Comfort with modern ML infrastructure (e.g., Docker, CUDA, Kubernetes, experiment tracking tools such as Weights & Biases)
Benefits:
- company paid healthcare
- flexible spending accounts
- voluntary life insurance
- 401K matching
- uncapped vacation
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