ML) Capability Engineering Team Lead

Merck•Rahway, NJ

5d•$173,200 - $272,600•Hybrid

About The Position

The AI/ML Capability Engineering Team Lead supervises a cross-functionally embedded team of AI/ML Engineers and Data Scientists developing AI Natural Language Processing (NLP) and Agentic AI capabilities for therapeutic research and development. The role partners across the R&D pipeline and software technology stack to lead AI initiatives, influence AI strategy, and guide the team in building models and pipelines intended to solve real-world problems and improve patient outcomes. The position involves building, deploying, and publishing AI methods and agentic workflows for applications such as machine translation, content generation and document drafting, workflow optimization, data enrichment, literature mining, target and biomarker prioritization, and representation learning. The lead partners with stakeholders and product teams to design and iteratively improve solutions; evaluates and optimizes AI workflows; develops human-in-the-loop approaches; and proposes areas of focus. The role also collaborates with experts across R&D and informatics disciplines, tracks AI regulations and internal policies, stays current with AI/ML innovations, and uses AI coding assistants responsibly. The team lead presents plans and results to scientific and IT leadership, contributes to strategic planning, and supervises, mentors, and recruits AI/ML engineers and other professionals. The role calls for technical and leadership expertise across modern LLM and agentic architectures, software and data engineering, model deployment and operations, AI governance, and production-ready solution development. The role is based primarily in Rahway, New Jersey, with a hybrid work arrangement and 10% travel. Domestic relocation is indicated; visa sponsorship is not available. Employment status is regular.

Requirements

A PhD in data science, AI/ML/LLM/Agentic system engineering, computer science, semantic engineering, a related discipline, or a scientific field and 5 years of relevant industry experience; or an M.S. in a similar field with 6 years of relevant industry experience; or a B.S. in a similar field with 7 years of relevant industry experience.
5 years of technical leadership experience with AI/ML, NLP, or Agentic AI projects or products.
2 years of experience supervising team members.
Excellent technical and non-technical communication, planning, teamwork, and leadership skills.
Ability to critically evaluate new problems and AI/ML solution architecture and implementation.
Strategic mindset, including the ability to envision how AI/ML and software solutions may generalize to new application areas.
Deep understanding of modern LLM and Agentic architectures, including retrieval-augmented generation (RAG), tool calling/Model Context Protocol (MCP), structured extraction, and agent orchestration.
Fluency in Python, Git-based version control and collaboration, environment management (such as uv or Docker), and at least one ML framework (such as PyTorch or vLLM).
Excellent statistical analysis skills, including understanding the implications of class imbalance.
Experience with scalable engineering frameworks such as Apache Spark and orchestrator frameworks such as Airflow.
Experience with Agentic AI protocols and standards such as MCP, A2A, and A2UI, and with building production-ready software and AI solutions.
Experience with harness optimization approaches, such as auto-research.
Experience with AI/ML model deployment and operations and modern software deployment standards, including DevOps and CI/CD practices.
Experience with agentic system development (such as LangGraph), text processing (such as regular expressions, information retrieval, and search systems), semantic engineering (such as RDF), and/or data engineering.
Familiarity with enterprise AI governance, data privacy boundaries, validation, fairness, and related ethical AI topics.
Passion for technology, science, biomedicine, and mentorship.
Required skills listed: Apache Airflow, Apache Spark, Artificial Intelligence (AI), Data Engineering, Git, IBM watsonx.governance, Image Processing, LangGraph, Machine Learning (ML), Natural Language Processing (NLP), Orchestrate, Python, Software Development Life Cycle (SDLC), Solution Architecture, System Designs, System Integration, Systems Engineering, and Testing.

Responsibilities

Lead and supervise a cross-functionally embedded team of AI/ML Engineers and Data Scientists developing AI, NLP, and Agentic AI capabilities for therapeutic R&D.
Build, deploy, and publish innovative and robust AI methods and agentic workflows, including applications in machine translation, content generation, document drafting, workflow optimization, data enrichment, literature mining, target and biomarker prioritization, and representation learning.
Partner with stakeholders and product teams to ideate, design, build, and iteratively improve solutions.
Evaluate and optimize machine learning and AI workflows using standard and novel techniques, and develop human-in-the-loop AI approaches.
Propose areas of focus and solutions to explore.
Collaborate with experts across the R&D pipeline and across informatics and AI/ML disciplines, including image processing, bioinformatics, representation learning, and decision sciences.
Track and help adhere to evolving AI regulations and internal policies, including data privacy and risk mitigation requirements.
Stay current with innovations in AI/ML and Agentic AI, and use AI coding assistants in innovative and responsible ways.
Present plans and results to scientific and IT leadership and provide input on strategic planning.
Supervise, mentor, and recruit AI/ML engineers and other professionals.

Benefits

Medical, dental, vision healthcare, and other insurance benefits for employees and family.
Retirement benefits, including 401(k).
Paid holidays, vacation, and compassionate and sick days.
Eligible for annual bonus and long-term incentive, if applicable.

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