Machine Learning Scientist

Responsibilities

• Design, build, and maintain agentic systems for automated data acquisition from public and proprietary biomedical data sources
• Develop LLM-based pipelines for data cleaning, normalization, and formatting across diverse data modalities
• Implement automated quality-control workflows to detect anomalies and enforce data standards
• Evaluate and iterate on agent architectures, prompting strategies, and tool-use patterns
• Collaborate with ML scientists to translate data requirements into scalable processing systems
• Monitor and maintain data pipelines in production, diagnosing failures and improving robustness
• Document data provenance, processing decisions, and quality metrics

Requirements

• Master's or PhD in a computational STEM field, or equivalent industry experience
• Strong Python engineering skills with experience in production-quality software
• Hands-on experience with LLM APIs and agentic patterns (tool use, orchestration, multi-step reasoning)
• Familiarity with biomedical or chemical data sources and formats (e.g., PDB, UniProt, ChEMBL, SDF/MOL, FASTA)
• Proficiency in data engineering fundamentals including ETL design and data validation

Preferred Qualifications

• Experience with agent orchestration frameworks
• Familiarity with cloud infrastructure and workflow orchestration (AWS, Docker, Kubernetes)
• Knowledge of multimodal biomedical data (small molecules, proteins, assays, images, omics, or clinical records)
• Experience with large-scale dataset construction for ML model training

About the Company

Iambic is a clinical-stage life-science and technology company developing novel medicines using its AI-driven discovery and development platform. The Iambic platform has demonstrated delivery of new drug candidates to human clinical trials with unprecedented speed across multiple target classes.