Machine Learning Scientist – Agentic Data Pipelines

Iambic Therapeutics

. Design, build, and maintain agentic systems for automated data acquisition from public and proprietary biomedical data sources .

Posted 5/7/2026full-timeBoston • Massachusetts • 🇺🇸 United StatesMid-LevelSenior💰 $148,000 - $210,000 per yearWebsite

Tech Stack

Tools & technologies

AWSCloudDockerETLKubernetesPython

About the role

Key responsibilities & impact

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
Evaluate and iterate on agent architectures, prompting strategies, and tool-use patterns to improve reliability and throughput
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

Requirements

What you’ll need

Master's or PhD in a computational STEM field, or equivalent industry experience
Strong Python engineering skills, including experience building and maintaining production-quality software
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)
Comfort with data engineering fundamentals: ETL design, data validation, and working with structured and unstructured data at scale
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

Benefits

Comp & perks

company paid healthcare
flexible spending accounts
voluntary life insurance
401K matching
uncapped vacation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

PythonLLM APIsETL designdata validationdata cleaningdata normalizationdata formattingagent orchestrationquality-control workflowslarge-scale dataset construction

Soft Skills

collaborationproblem-solvingcommunicationdocumentationanalytical thinking

Certifications

Master's degreePhD