Machine Learning Scientist — Large multimodal models

Iambic Therapeutics, Inc; Boston (MA); Hybrid; USD 100,000 - 150,000; Full time

Benefits offered by this job

Company paid healthcare

Flexible spending accounts

401K matching

Uncapped vacation

Job summary

Iambic Therapeutics, Inc. is seeking a Machine Learning Scientist to develop and scale their Enchant model for biomedical data. This role will involve architectural research, production deployment, and collaboration with scientists in drug discovery. Candidates should have a strong background in Python and PyTorch with experience in training transformer models at scale. Iambic offers competitive pay, healthcare, and a flexible work environment. This role can be remote or on-site in Boston, US.

Qualifications

• MS in ML/CS or equivalent experience is required.
• Strong Python and PyTorch experience is essential.
• Experience in training transformer models at scale is crucial.

Responsibilities

• Research and implement improvements to multimodal transformer models.
• Optimize training pipelines for efficiency and scalability.
• Collaborate with computational chemists and biologists.

Skills

Python

PyTorch

Deep learning models

Reproducible experimentation

Docker

CUDA

Kubernetes

Education

MS in ML/CS or a computational STEM field

PhD or equivalent industry experience

Tools

Weights & Biases

Job description

Job Summary

We are seeking a Machine Learning Scientist to join the Iambic team at Iambic Therapeutics. Our mission is to deliver better medicines through innovation in AI-based discovery technologies. In this role, you will research, develop, and scale Enchant — our multimodal transformer model trained on a wide variety of biomedical data — pushing the boundaries of what large-scale foundation models can achieve in drug discovery.

This role spans architecture research through to production deployment. You will design and evaluate new model architectures, develop hybrid modeling approaches, optimize training and inference at scale, and work with colleagues across ML and drug discovery to put these models into the hands of scientists making real therapeutic decisions.

We are hiring flexibly across levels, from Associate Scientist through Research Scientist II, depending on experience.

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.

PAY AND BENEFITS

We offer industry leading competitive pay, company paid healthcare, flexible spending accounts, voluntary life insurance, 401K matching, and uncapped vacation to our team. We are in a brand-new state-of-the art facility in beautiful San Diego with an onsite gym, dining, and easy access to great places to live and play.