[Remote] Machine Learning Scientist – Clinical Prediction

Note: The job is a remote job and is open to candidates in USA. Iambic is a clinical-stage life-science and technology company developing novel medicines using its AI-driven discovery and development platform. They are seeking a Machine Learning Scientist to design and implement clinical fine-tuning of their multimodal transformer model, Enchant, which is aimed at enhancing drug discovery through advanced data analysis and modeling.

Responsibilities

• Fine-tune large-scale multimodal transformer models for clinical and biomedical applications
• Identify, characterize, and utilize datasets that can deliver insights into pharmacokinetics (PK), pharmacodynamics (PD), toxicity, clinical adverse events, and clinical trial outcomes
• Develop and apply rigorous experimental approaches that account for multiple sources of potential leakage (split, metadata, trial-family, temporal, ontological, arm-comparator, etc.)
• Design and maintain benchmarking and evaluation frameworks that track model quality across models and tasks
• Build models with appropriate calibration, uncertainty quantification, and clinically meaningful evaluation metrics
• Collaborate with ML and software engineering colleagues to deploy and operationalize models
• Partner with clinical scientists and pharmacologists to ensure model development is grounded in drug discovery and development needs
• Communicate results to internal teams, external partners, and at conferences
• Generate high-quality research and engineering code: refactor, test, document, and package ML components to support team velocity

Skills

• MS in chemistry, bio/chemical engineering, or a computational STEM field with 3+ years of relevant industry or research experience, or PhD or equivalent industry experience demonstrating comparable depth
• Strong Python experience, including implementing and fine-tuning deep learning models
• Demonstrated experience in clinical science or working with clinical datasets
• Excellent Data Science skills (problem framing, data sourcing, extraction, cleaning, visualization, EDA, modeling, tuning, storytelling, etc.)
• Enough independence to own a workstream from data ingestion through evaluation
• Strong engineering habits: reproducible experimentation, appropriate control strategy, clean code, testing
• Comfort working with modern ML infrastructure (e.g., Docker, CUDA, Kubernetes, experiment tracking such as Weights & Biases)
• Experience building and deploying clinically relevant prediction models
• Familiarity with ClinicalTrials.gov/AACT data
• Experience with MedDRA, pharmacovigilance, or adverse event data
• Direct exposure to multi-task learning
• Hands-on experience with agentic data extraction
• HPC or large-scale computing experience

Benefits

• Company paid healthcare
• Flexible spending accounts
• Voluntary life insurance
• 401K matching
• Uncapped vacation
• Brand-new state-of-the art facility in beautiful San Diego with an onsite gym
• Dining
• Easy access to great places to live and play

Company Overview