Machine Learning Scientist — Large multimodal models

Key Responsibilities

• Research and implement architectural improvements to large-scale multimodal transformer models for biomedical applications
• Investigate hybrid modeling approaches that combine learned representations with domain-informed structure or inductive biases
• Optimize training pipelines for efficiency, stability, and scalability across many-GPU clusters
• Develop and apply inference optimization techniques to support deployment in interactive discovery workflows
• Design and maintain benchmarking and evaluation frameworks that track model quality across modalities and downstream tasks
• Collaborate with ML and software engineering colleagues to deploy and operationalize models
• Partner with computational chemists, medicinal chemists, and biologists to ensure model development is grounded in drug discovery needs
• Communicate results to internal teams, external partners, and at conferences
• Write high-quality research and engineering code: refactor, test, document, and package ML components to support team velocity

Depending on level

• Mentor interns and junior team members through technical guidance, code reviews, and best practices in ML experimentation
• Contribute to the strategic research roadmap for Enchant and related multimodal technologies

Qualifications

Required

• MS in ML/CS or a computational STEM field with relevant industry or research experience, or PhD or equivalent industry experience demonstrating comparable depth
• Strong Python and PyTorch experience, including implementing and training deep learning models end-to-end
• Demonstrated experience training transformer models at scale
• Strong engineering habits: reproducible experimentation, clean code, testing, and performance-minded debugging
• Comfort working with modern ML infrastructure (e.g., Docker, CUDA, Kubernetes, experiment tracking such as Weights & Biases)

Desired

• Experience with multimodal or multi-task model architectures
• Training and inference optimization (e.g., mixed precision, kernel optimization, quantization, distributed strategies)
• Familiarity with biomedical, chemical, or biological data domains
• Distributed training at scale
• HPC or large-scale training operations experience

Location

Remote (US or UK). On-site available in Bristol, UK and Boston, US.

ABOUT IAMBIC THERAPEUTICS

Iambic is a clinical-stage life-science and technology company developing novel medicines using its AI-driven discovery and development platform. Based in San Diego and founded in 2020, Iambic has assembled a world-class team that unites pioneering AI experts and experienced drug hunters. The Iambic platform has demonstrated delivery of new drug candidates to human clinical trials with unprecedented speed and across multiple target classes and mechanisms of action. Iambic is advancing a pipeline of potential best-in-class and first-in-class clinical assets, both internally and in partnership, to address urgent unmet patient need. Learn more about the Iambic team, platform, pipeline, and partnerships at iambic.ai.

MISSION & CORE VALUES

Our mission is to deliver better medicines through innovations in AI-based discovery technologies. The culture and work at Iambic Therapeutics are profoundly strengthened by the diversity of our people and our differences in background, culture, national origin, religion, sexual orientation, and life experiences. We are committed to building an inclusive environment where a diverse group of talented humans work together to discover therapeutics and create technologies.