Senior AI/ML Engineer

Role Summary

Senior AI/ML Engineer to join Crinetics' Enterprise Solutions & Innovation group in San Diego, CA. This role will shape the AI/ML strategy, evaluate and implement solutions, and demonstrate the value of data-driven decision-making across the organization.

Responsibilities

• Strategic Development: Collaborate with the Executive Director of Enterprise Solutions & Innovation to define and execute the company's AI/ML roadmap. Identify and prioritize high-impact use cases across research, clinical development, manufacturing, and commercial operations.
• Solution Evaluation and Implementation: Lead the technical evaluation of internal and external AI/ML solutions. Design, build, and deploy scalable machine learning models on the Azure/Databricks platform. Assess and integrate vendor-provided AI/ML technologies to meet scientific and business requirements.
• Cross-Functional Collaboration: Partner with stakeholders from R&D, Clinical Operations, Regulatory Affairs, and other departments to translate needs into data science questions and solutions. Serve as a subject matter expert on AI/ML and provide guidance and training to colleagues.
• Data and Infrastructure: Work with IT and data engineering teams to ensure data availability and quality for AI/ML initiatives. Contribute to data infrastructure and governance practices.
• Innovation and Research: Stay current with advances in ML/AI and data science. champion a culture of innovation by exploring novel approaches and technologies to address business challenges.

Qualifications

• Required: Education — Master's or Ph.D. in Computer Science, Data Science, Statistics, Computational Biology, or a related quantitative field.
• Required: Experience — 8–10 years with 3–5 years of hands-on data science and ML, with a proven record of developing and deploying AI/ML models in a corporate environment.
• Required: Technical Skills —
  • Expert proficiency in Python or R
  • Extensive experience with ML libraries/frameworks (Scikit-Learn, TensorFlow, PyTorch)
  • Strong SQL and experience with relational and non-relational databases
  • Hands-on experience with Azure and Databricks
  • Software engineering practices including Git, testing, and CI/CD
• Required: Soft Skills — Excellent problem-solving and analytical abilities; strong communication and interpersonal skills; ability to convey complex concepts to non-technical audiences; independent and collaborative work style; strategic, innovative mindset.
• Preferred: Experience in the biopharmaceutical or biotechnology industry
• Preferred: Familiarity with drug discovery and development processes
• Preferred: Experience with life sciences data sources (genomic data, clinical trial data, real-world evidence)
• Preferred: Knowledge of GxP regulations and experience in a regulated environment

Additional Requirements

• Travel: Up to 5% of time may be required