Iambic Therapeutics
Machine Learning Scientist — Agentic data pipelines
Boston Office
Sponsorship not specifiedDetected 77 days ago
PythonAWSCloud PlatformsDockerKubernetesMachine LearningData EngineeringNLPLLMsAgentic AIAI OrchestrationAuditingClinical Trials
About the role
- We are seeking a scientist to join our team at Iambic Therapeutics, working on data acquisition and curation for Enchant https://www.iambic.ai/post/enchant, our multimodal transformer model trained at scale on a wide variety of biomedical data.
- This role is ideal for candidates who combine strong software engineering instincts with scientific understanding of biomedical data, and who are excited about using LLMs as tools to solve practical data problems.
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 (e.g., molecular, genomic, clinical, literature)
- Implement automated quality-control workflows that detect anomalies, flag inconsistencies, and enforce data standards
- Collaborate with ML scientists on the Enchant team to understand data requirements and translate them into scalable acquisition and processing systems
- Monitor and maintain data pipelines in production, diagnosing failures and improving robustness over time
- Document data provenance, processing decisions, and quality metrics to support reproducibility and auditing
- Strong Python engineering skills, including experience building and maintaining production-quality software
- Comfort with data engineering fundamentals: ETL design, data validation, and working with structured and unstructured data at scale
Requirements
- Hands-on experience with LLM APIs (e.g., Claude, GPT) and agentic patterns such as tool use, orchestration, and multi-step reasoning
- Familiarity with biomedical or chemical data sources and formats (e.g., PDB, UniProt, ChEMBL, SDF/MOL, FASTA, or similar)
- Experience with agent orchestration frameworks
- Familiarity with cloud infrastructure and workflow orchestration (e.g., AWS, Docker, Kubernetes)
- Knowledge of multimodal biomedical data-spanning small molecules, proteins, assays, images, 'omics, and/or clinical records
- Experience with large-scale dataset construction or curation for ML model training
Skills
- Evaluate and iterate on agent architectures, prompting strategies, and tool-use patterns to improve reliability and throughput
Benefits
- We offer industry leading competitive pay, company paid healthcare, flexible spending accounts, voluntary life insurance, 401K matching, and uncapped vacation to our team.
Company info
- 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.
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