Machine Learning Engineer Lead

Key Responsibilities
Define reference architectures for LLM, machine learning, and agent-based systems across products. Design high-availability and low-latency inference platforms capable of operating at global scale. Establish reusable platform components for model lifecycle management, deployment, monitoring, and operationalization. Architect scalable AI platforms supporting large-scale distributed ML systems and enterprise AI workloads. Architect multi-step, reasoning-driven agentic AI systems. Design orchestration patterns for tool use, API invocation, and structured function calling.

Lead the implementation and governance of Model Context Protocol (MCP) servers to standardize tool integration and context management. Define guardrails, permissions, security controls, and audit mechanisms for enterprise-safe AI systems. Establish and maintain best practices for MLOps, CI/CD, observability, scalability, and system reliability. Design and implement scalable inference systems using containerization and Kubernetes. Drive the deployment and optimization of LLM, Generative AI, and RAG solutions in production environments.

Design cloud-based AI/ML architectures across AWS, Azure, or Google Cloud Platform. Establish technical standards and architectural patterns for AI/ML and agentic systems across engineering teams. Embed Responsible AI principles into platform architecture and engineering practices. Provide technical leadership, mentorship, and guidance to senior engineers and engineering teams. Collaborate with cross-functional teams to influence technical direction and ensure alignment with enterprise AI platform strategy. Support people management, leadership, and team development activities as required.

Required Qualifications
10+ years of experience
Bachelors Degree

Skills
Machine Learning Systems
Large Language Models (LLMs)
Python Development
Cloud AI/ML Architectures
Kubernetes
Agentic AI Systems Design
Model Context Protocol (MCP) Servers
Large-scale Distributed ML Systems
MLOps
High-availability AI/ML Architectures
Technical Leadership
Cross-functional Collaboration
People Management
Architecture Definition
Technical Standards Establishment
Responsible AI Principles

Schedule
Start date: 2026-08-26