AI/ML Engineer, Drug Discovery at BioPhase AI/ML Engineer, Drug Discovery at BioPhase in San Diego, California Posted in 2 days ago.

Type:

full-time

AI/ML Engineer, Drug Discovery Status:

Contract-to-hire Comp:

$45-$70/hr DOE SD local candidates highly preferred Biotech/Drug discovery AI/ML applications a MUST Role Summary 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. 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. What You'll Do 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. What We're Looking For 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.