Job Description

Join a global leader in legal, regulatory, and business information as a Senior Machine Learning Engineer supporting a next-generation AI Platform team. This is a 6–12 month remote contract-to-hire opportunity. You’ll help build and scale enterprise AI platforms leveraging LLMs, RAG architectures, agentic AI frameworks, distributed ML systems, Kubernetes, Python, and cloud technologies that power mission-critical applications used around the world.

This is a rare opportunity to influence the future of enterprise AI at scale. The team is building the foundational infrastructure behind advanced AI products and is looking for someone who can architect complex AI systems, establish engineering standards, and guide the evolution of agentic workflows across the organization. 

Contract Duration: 6–12 Months (Contract-to-Hire)

Required Skills & Experience

· PhD in a relevant field or 8+ years of experience with a Master’s degree or 12+ years of experience with a Bachelor’s degree
· 8+ years building production-scale machine learning systems
· Extensive experience with LLMs, Generative AI, and RAG architectures
· Strong Python development background
· Experience architecting distributed systems in AWS, Azure, or GCP
· Hands-on experience with Kubernetes, containerization, and scalable inference platforms
· Experience developing agentic AI systems and tool orchestration frameworks
· Experience implementing or managing MCP servers and structured tool-calling architectures
· Deep understanding of MLOps, observability, reliability, and model evaluation
· Strong system design and architecture experience

Desired Skills & Experience

· Experience building enterprise AI platforms at scale
· Background with vector databases and semantic search technologies
· Responsible AI and governance experience
· Proven ability to influence cross-functional technical direction
· Experience mentoring senior engineers
· Strong communication and stakeholder management skills
· Experience operating within highly regulated or enterprise environments

What You Will Be Doing

Tech Breakdown
· 40% LLMs, RAG, and Agentic AI Systems
· 30% Distributed Systems & Cloud Architecture (AWS/Azure/GCP)
· 20% MLOps, Platform Engineering & Reliability
· 10% Technical Leadership & Mentorship

Daily Responsibilities
· 80% Hands On
· 5% Management Duties
· 15% Team Collaboration

You’ll design scalable AI platform architecture, build enterprise-grade agent systems, define standards for tool orchestration and MCP integration, establish AI governance and security controls, improve ML platform reliability, and partner with engineering leaders to shape the long-term AI strategy across the organization.