Associate Director, Ai/ml Engineering

Merck Merck · Pharma · MA

Associate Director, AI/ML Engineering at Merck, focusing on building and deploying AI/ML tools and pipelines for drug discovery. The role involves leading the design, development, deployment, monitoring, and maintenance of reusable software components for AI/ML workflows, supporting AI/ML Researchers and Data Scientists, and staying updated on AI/ML advancements. Requires experience with Python, Torch, AWS, MLFlow, Docker, GitHub, and CI/CD, particularly with transformer-based Foundation Models and representation learning. Experience with the full SDLC for Python Packages and Docker images following DevSecOps best practices is also required. Interest in life sciences and agentic Co-scientist environments is noted.

What you'd actually do

  1. 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
  2. Collaborate in a highly-matrix environment to identify research questions, scope data requirements, and develop appropriate AI/ML solutions
  3. Provide tactical and strategic technical support for AI/ML Researchers and Data Scientists
  4. 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

Skills

Required

  • Python
  • Torch
  • AWS
  • MLFlow
  • Docker
  • GitHub
  • GitHub Actions CI/CD workflows
  • transformer-based Foundation Models
  • representation learning
  • full SDLC of maintaining Python Packages and Docker images
  • DevSecOps best practices
  • Agile SDLC
  • Artificial Intelligence (AI)
  • Biological Sciences
  • Cross-Functional Collaboration
  • Database Design
  • Data Engineering
  • Data Modeling
  • Data Science
  • Data Visualization
  • Foundation Models
  • Life Science
  • Machine Learning (ML)
  • Machine Learning Algorithms
  • Python Software Development
  • PyTorch
  • Software Development
  • Stakeholder Relationship Management
  • Teamwork
  • Transformer Model
  • Willingness to Learn

Nice to have

  • multi-omics
  • imaging data
  • Claude Code
  • Databricks
  • GCP
  • Databricks Platform
  • Google Cloud Platform (GCP) for Machine Learning
  • Imaging Analysis
  • Omics

What the JD emphasized

  • 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

Other signals

  • building/deploying/scaling novel AI/ML pipelines
  • transformer-based Foundation Models
  • representation learning
  • reusable software components
  • reliable/scalable AI/ML workflows, tools, and applications