Lead Machine Learning Engineer

Motion Recruitment Partners LLC.

Raleigh, NC, United States

6 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

10 years minimum

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Microsoft Azure Continuous Integration Distributed Systems Python (Programming Language) Machine Learning Google Cloud Cloud Platform System Large Language Models Multi-Agent Systems

+8 more

Model Validation Reliability of Systems Generative AI Containerization AI Platforms Kubernetes Machine Learning Operations Virtual Agents

Job description

We are seeking a Sr. Machine Learning Engineer to define and lead the architecture of scalable AI/ML and agentic systems across our global product portfolio. This is a senior technical leadership role for someone who thrives at the intersection of:

Large-scale distributed ML systems
LLM and RAG architectures
Agentic AI frameworks and tool orchestration
Enterprise platform engineering

You will shape the long-term AI platform strategy and establish technical standards that impact millions of users

What You’ll

Do Architect Scalable AI Platforms
Define reference architecture for LLM, ML, and agent-based systems across products
Design high-availability, low-latency inference platforms for global scale
le.Establish reusable platform components for model lifecycle, deployment, and monitori
Lead Agentic AI & Tool Ecosystems
Architect multi-step, reasoning-driven agent systems
Design orchestration patterns for tool use, API invocation, and structured function calling
Lead implementation and governance of Model Context Protocol (MCP) servers to standardize tool integration and context management
Define guardrails, permissions, and audit mechanisms for enterprise-safe AI systems
Elevate Engineering Standards. Set best practices for MLOps, CI/CD, observability, and system reliability
Embed Responsible AI principles across platform architecture
Mentor senior engineers and influence technical direction across teams

Requirements

10+ yrs of experience with Master’s degree or 12+ yrs of experience with bachelor degree
10+ years building production-grade ML systems at scale
Extensive experience with LLMs, generative AI, and RAG systems in real-world deployments
Proven expertise designing distributed systems in cloud environments (AWS, Azure, or Google Cloud Platform)
Hands-on experience with Kubernetes, containerization, and scalable inference systems
Experience designing agentic systems and tool orchestration frameworks
Experience implementing or governing MCP servers or structured tool-calling architectures
Technical Strength/Strong Python engineering background
Experience with vector databases and search systems
Deep understanding of model evaluation, reliability, and monitoring
Strong architectural judgment and systems thinking
Leadership/Demonstrated ability to influence technical direction across teams
Strong communication skills and executive presence
Experience mentoring senior engineers or leading cross-functional initiatives

About the company

Our Client serves customers in over 150 countries with trusted legal, regulatory, and business information. They are transforming the legal industry through cutting-edge AI, scalable data platforms, and intelligent research systems that power high-stakes decision-making for legal professionals worldwide. Their Global AI Platform Team builds the foundational infrastructure behind next-generation AI products, including LLM-powered research assistants, retrieval systems, and enterprise-grade agentic workflows.