Senior Lead Machine Learning Engineer, Agentic AI

Upwork
Full-timeLead

Tech Stack

PythonGoJavaJavaScriptMCPDistributed SystemsMicroservices

Agent Workflow

Design multi-agent systems with planning, tool-use, memory, and reflection capabilities. Implement protocol-aware agents compatible with frameworks like MCP.

About the Role

Upwork (Nasdaq: UPWK) is establishing its first international operational hub in Lisbon, Portugal, with the new office expected to be fully operational by Q4 2026. They are seeking a Senior Lead Machine Learning Engineer to architect, ship, and scale the next generation of agentic intelligence.

Key Responsibilities:

  1. Agentic Intelligence Development - Design multi-agent systems with planning, tool-use, memory, and reflection capabilities; implement protocol-aware agents compatible with frameworks like MCP
  2. LLM Training & Evaluation - Lead data curation and model adaptation (SFT, DPO, RLHF); build evaluation frameworks measuring success rates, latency, and hallucination metrics
  3. Platform Infrastructure - Architect low-latency services for inference and orchestration; ship production APIs/SDKs with strong SLOs and cost optimization; optimize through quantization and model routing
  4. Technical Leadership - Mentor senior engineers, influence roadmaps, publish guidance and reference architectures; define KPIs and drive cross-functional collaboration

Requirements:

  • 8-12+ years applied ML/ML systems; 4+ years building LLM products with production agentic workflows
  • Hands-on mastery of LLM adaptation (prompting, tool/function calling), data curation, and safety/guardrails
  • Strong distributed systems fundamentals and microservices experience
  • Python fluency; Go/Java/JavaScript proficiency a plus
  • Experience designing evaluation suites with task-based and rubric-based metrics
  • Cross-functional leadership and mentoring track record
  • Expertise in agent frameworks (e.g., MCP protocol)

Employment Note: Initially contracted through a partner pending Lisbon hub establishment (Q4 2026), with potential direct employment transition afterward.

Published: February 3, 2026.

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