Job Description
Our Artificial Intelligence Machine Learning (AI/ML) capabilities are critical accelerators to our mission to delivering towards inventing new medicines that save and improve lives. Core to the Data, AI, and Genome Sciences (DAGS) function is an AI/ML-first approach to improving target and biomarker discovery, validation and selection and elucidating complex disease mechanisms. As Associate Director, AI/ML Engineering, you will build state-of-the-art AI/ML tools and pipelines to accelerate scientific discovery. You will be part of a cross-functional team of computational biologists, bioinformaticians, data scientists, software engineers, and other AI/ML engineers that strive to identify therapeutic targets.
Primary Responsibilities include:
- Lead the design, development, deployment, monitoring, and maintenance of reusable software components that can be integrated into reliable/scalable AI/ML workflows, tools, and applications
- Collaborate in a highly-matrix environment to identify research questions, scope data requirements, and develop appropriate AI/ML solutions
- Provide tactical and strategic technical support for AI/ML Researchers and Data Scientists
- Stay up-to-date with the latest advancements in AI/ML research and operations to proactively propose innovative approaches aligned with industry standards that enhance our internal capabilities
Required Experience and Skills:
Education requirements:
One of the following credentials:
- PhD in Computer Science, Physics, Electrical Engineering, Biomedical Engineering, Bioinformatics, Computational Biology, Genetics/Genomics, or a related STEM field with 4+ years post-graduate academic medical or industry experience
- Masters with 7+ years of experience, or
- Bachelors with 11+ years of experience
Experience & Skills:
- Candidates must be an Engineer with a passion to focus relentlessly on the enablement of their teammates with best-in-class tools and pipelines in a fast-paced industry environment
- Candidates must have excellent communication/interpersonal skills and a team-focused collaborative mindset to provide technical support to code-heavy AI/ML Engineers and Data Scientists and to collaborate more broadly in a multi-disciplinary department
- Candidate must be a self-starter and be able to lead projects independently
- Candidates must have experience with Python, Torch, AWS, MLFlow, Docker, GitHub, and GitHub Actions CI/CD workflows
- Candidates must have experience building/deploying/scaling novel AI/ML pipelines, particularly transformer-based Foundation Models and representation learning to support downstream tasks
- Candidates must have experience with the full SDLC of maintaining Python Packages and Docker images following modern DevSecOps best practices
- Willingness to learn from others and to teach others
- Excellent communication skills and ability to work collaboratively in multi-disciplinary team
- Interest in life sciences problems and how agentic Co-scientist environments can accelerate discovery
- Experience with multi-omics and imaging data is nice to have
- Experience with Claude Code, Databricks, and GCP is nice to have
Required Skills:
Agile SDLC, Artificial Intelligence (AI), Biological Sciences, Cross-Functional Collaboration, Database Design, Data Engineering, Data Modeling, Data Science, Data Visualization, Foundation Models, GitHub Actions, Life Science, Machine Learning (ML), Machine Learning Algorithms, Python Software Development, PyTorch, Software Development, Stakeholder Relationship Management, Teamwork, Transformer Model, Willingness to Learn
Preferred Skills:
Amazon Web Services (AWS), Databricks Platform, Google Cloud Platform (GCP) for Machine Learning, Imaging Analysis, Omics
