Director, AI/ML Engineering Lead

Job Description

Director, Data Science and AI, Engineering Lead

Our Artificial Intelligence and Machine Learning (AI/ML) capabilities are vital catalysts for our mission to invent new medicines that save and enhance lives.  The Data, AI & Genome Sciences (DAGS) function at our organization adopts an AI/ML-first approach to enhance target and biomarker discovery by driving the understanding of complex disease mechanisms.  As the Director of Data Science and AI, Engineering Lead, you will leverage your expertise in Software Engineering, Data Engineering, Data Science, Machine Learning Engineering, and High-Performance Scientific Computing to manage the full Software Development Lifecycle (SDLC) of custom AI/ML applications that accelerate the pace of therapeutic target discovery by DAGS Data Scientists, Machine Learning Scientists, Computational Biologists, Biologists, and Researchers.  You will also forge strong cross-functional partnerships with IT solution experts to maintain access to state-of-the-art compute infrastructure required to remain at the forefront of innovation. You will report to the Executive Director and Head of AI/ML.

Primary Responsibilities:

• Manage the full SDLC of custom AI/ML applications enabling Data Scientists, Computational Biologists, and Researchers to decode disease biology to drive novel target and biomarker discovery.

• Enable rapid prototyping, fast iteration, and user-driven enhancements of AI/ML application.

• Partner with DAGS AI/ML team to maintain and scale an experimental compute environment integrating massive Multi-modal FAIR Data and Knowledge Graph infrastructure with high-performance AWS/Databricks-based AI/ML experimental workstreams.

• Drive strategy for high-performance GPU cluster compute to de-risk reliance on any one solution and to ensure that DAGS AI/ML Team members maintain access to scalable state-of-the-art GPU clusters.

• Provide technical support to DAGS AI/ML Data Scientists, AI/ML Researchers, and AI/ML Engineers to ensure that they can do their work efficiently and effectively. 

• Partner with many DAGS and IT stakeholders in a complex, highly matrixed, fast-paced environment to plan, build, test, deploy, monitor, and maintain the reliable compute infrastructure and software tools to deliver high-impact machine learning applications and ring-fence and de-risk deliverables.

Required Experience and Skills:

• PhD in a relevant field such as Computer Science, Electrical Engineering, Physics, or a related discipline, with 6+ years of industry experience, MS with 9+ years of experience, or BS with 12+ years of experience

• Experience building, deploying, and monitoring AI/ML applications.

• Fluency in AWS, Databricks, MLFlow, Python, Torch, R, Spark, React, Java, Docker, Bash, GitHub, CI/CD, Redshift, Dev/Staging/Prod Deployments, Jira, Confluence.

• Experience pre-train/fine-tuning/evaluating transformer-based Foundation Models.

• Hands-on experience with Knowledge Graphs. 

• Familiarity with State-Space and Graphical Neural Network Models is a plus.

• Hands-on experience with biological data is a plus.

• Excellent communication skills and ability to work collaboratively in a fast-paced, multi-disciplinary team.

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