Director, Translational Machine Learning

Iambic Therapeutics, Inc•San Diego, CA

About The Position

We are seeking a Director of Translational ML to join Iambic Therapeutics and serve as the connective tissue between our machine learning capabilities and the crucial questions arising from clinical and near-clinical drug discovery programs. In this role, you will shape and scale a translational ML function that brings the full power of modern ML — across omics, imaging, and other biomedical data modalities — to bear on patient population selection, drug candidate selection, and biomarker discovery. This is a hands-on leadership role. You will personally drive technical work in translational ML while managing a small team of ML scientists focused on imaging and omics modalities. Equally important, you will ensure that translational biology data and tasks are made legible to our ML models and teams, and that ML outputs are translated into actionable insights for drug discovery decision-makers. You will be a key contributor to the development roadmap for Enchant, Iambic's multimodal transformer model, feeding back translational requirements and use cases that shape the model's evolution. The ideal candidate combines deep ML expertise with genuine fluency in translational biology, and has the judgment and communication skills to operate credibly across both worlds.

Requirements

PhD in machine learning, computational biology, bioinformatics, or a related computational STEM field
Demonstrated expertise applying ML methods to biomedical or translational problems, including hands-on experience with omics data and biomedical imaging modalities
Industry experience in drug discovery or pharmaceutical R&D, with exposure to translational workflows such as biomarker discovery, patient stratification, or drug candidate selection
Ability to grapple with conceptual complexities of experimental design across diverse biological data types
Strong communication skills and a track record of working effectively across ML and biology/chemistry teams
Experience managing or building small technical teams

Nice To Haves

Breadth across multiple omics platforms (e.g., bulk and single-cell transcriptomics, proteomics, metabolomics, epigenomics)
Breadth across multiple imaging platforms (e.g., histopathology including H&E, cellular imaging, high-content screening)
Experience with clinical trial data, including retrospective analysis and biomarker qualification
Experience with foundation models or large-scale representation learning in biological applications
Experience translating between ML and non-ML stakeholders in a drug discovery setting

Responsibilities

Define and execute a translational ML strategy spanning omics, imaging, and other biomedical data modalities, in close partnership with translational biology, clinical, and ML leadership
Directly contribute to technical work: experimental design, model development, analysis, and interpretation of translational ML outputs in support of active drug programs
Manage a team (initially 2–3 ML scientists) working on imaging and omics applications; hire for emerging needs as the function scales
Translate clinical and translational biology questions into well-posed ML problems, and translate ML results back into actionable recommendations for drug discovery teams
Serve as a strategic voice into the Enchant development roadmap, ensuring that translational use cases, data requirements, and evaluation criteria inform model priorities
Co-design experiments and data collection strategies with translational biology colleagues to maximize the utility of biomedical data for ML modeling
Establish evaluation frameworks that connect ML model performance to clinically meaningful endpoints and decision criteria
Communicate translational ML results and strategy to internal stakeholders, partners, and at scientific conferences