Job Description
AI/ML Engineer, Drug Discovery
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Status: Contract-to-hire
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Comp: $45-$70/hr DOE
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SD local candidates highly preferred
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Biotech/Drug discovery AI/ML applications a MUST
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Role Summary
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We're looking for a hands-on AI/ML Engineer to support drug discovery research through applied data science, machine learning, and informatics. This is a strong fit for someone who enjoys working directly with scientists, translating open-ended research questions into practical models and tools, and building workflows that hold up under real use.
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The role spans the full solution lifecycle — from data preparation and exploratory analysis through feature engineering, model development, validation, and deployment — with room to grow into production AI systems, LLM-based applications, and agentic workflows as the work evolves.
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What You'll Do
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- Work directly with research scientists to scope high-value problems and turn scientific questions into analytical or ML approaches.
- Build, test, and refine predictive models using both structured and unstructured scientific data.
- Design reproducible pipelines for ingesting, cleaning, integrating, and preparing data, including feature generation and quality checks.
- Apply data science and cheminformatics techniques to support discovery research and decision-making.
- Run exploratory analyses, communicate findings clearly, and recommend suitable modeling strategies.
- Write clean, maintainable Python and SQL, contributing to shared analytical tools, services, and APIs.
- Partner with engineers to bring models and workflows into stable production or research environments.
- Apply solid practices around experiment tracking, model versioning, testing, documentation, monitoring, and retraining.
- Contribute to AI-enabled applications — including LLM, copilot, or agent-based tools — where they fit the use case.
- Document data sources, assumptions, methods, and results for both technical and scientific audiences.
- Balance fast iteration with data quality, reproducibility, and operational reliability.
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What We're Looking For
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- Bachelor's degree in computer science, data science, mathematics, statistics, computational science, cheminformatics, bioinformatics, or a related quantitative field.
- 4+ years of relevant experience applying data science, machine learning, informatics, or software engineering to real-world problems.
- Solid hands-on skills in Python and SQL, along with common data analysis and ML libraries.
- Track record preparing complex datasets, engineering features, building models, and evaluating performance.
- Ability to turn ambiguous scientific or business questions into clear, actionable technical plans.
- Experience with reproducible workflows and standard engineering practices — version control, testing, code review.
- Strong written and verbal communication, including explaining technical work to non-technical or scientific audiences.
- A collaborative style, genuine curiosity, and comfort working in a fast-moving research setting.
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