Senior Lead Machine Learning Engineer, Agentic AI

Upwork Inc.'s (Nasdaq: UPWK) family of companies connects businesses with global, AI-enabled talent across every contingent work type including freelance, fractional, and payrolled. This portfolio includes the Upwork Marketplace and Lifted.

We're seeking a Senior Lead Machine Learning Engineer to architect, ship, and scale the next generation of agentic intelligence across Upwork. You will lead end-to-end development of AI agents and the platform that powers them, from LLM training and evaluation to runtime orchestration, safety, and developer APIs. This is a hands-on, high-impact role at the intersection of applied research and platform engineering.

Responsibilities

• Build Agentic Intelligence. Design and implement multi-agent systems (planning, tool-use, memory, debate/critique, reflection) with robust guardrails and recovery strategies
• Develop protocol-aware agents and services that interoperate cleanly with developer tooling (e.g., agent frameworks and protocols such as MCP)
• Own reliability at scale: deterministic execution where needed, idempotency, timeouts/retries, and evaluation-driven iteration on agent behavior
• Train, Align, and Evaluate LLMs for Agents. Lead data strategy and curation for agent tasks; drive SFT, DPO, RLHF/RLAIF, and safety tuning tailored to multi-tool, multi-step workflows
• Stand up evaluation harnesses for functional, task, and longitudinal metrics (success rate, time-to-completion, hallucination/escape rates, cost/latency)
• Build policy-driven guardrails; partner with Legal/Security on data governance and privacy
• Engineer Agentic Platform Backend Infrastructure. Architect low-latency inference, retrieval, and orchestration services (streaming, event-driven pipelines; scalable queues; caching; batching) with strong SLOs
• Ship production-grade services (APIs/SDKs, auth, rate limiting, observability) that make agent features easy to integrate for internal and external developers
• Optimize cost/performance via quantization, distillation, model-routing, and autoscaling
• Lead, Partner, and Uplevel the Ecosystem. Provide technical leadership across research, product, and platform teams; mentor senior ICs

What it takes to catch our eye

• 8-12+ years in applied ML/ML systems with 4+ years building LLM-powered products; proven delivery of agentic workflows in production
• Hands-on mastery of LLM adaptation (prompting, tool/function calling), data curation, and safety/guardrails
• Strong software fundamentals (distributed systems, transactions, consistency, resiliency)
• Fluency with Python; proficiency in one of Go/Java/Javascript a plus. Experience with container orchestration, messaging/streaming, and observability stacks
• Experience designing eval suites for agents and closing the loop from evals to training to runtime policy
• Familiarity with agent frameworks and protocols (e.g., MCP; API/SDK design for developer productivity)

This position will initially be employed through a partner to ensure a seamless hiring process while we establish the Toronto hub. Once the hub is established, there may be opportunities to transition to direct Upwork employment.