Upwork

Lead Machine Learning Engineer / Applied Scientist

Toronto, Ontario, Canada · Contract

Sponsorship not specified$179k-$303kDetected 37 days ago

Machine LearningRAGA/B TestingResearch

About the role

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.
Learn more about the Upwork Marketplace at Upwork.com and follow us on LinkedIn, Facebook, Instagram, TikTok, and X; and learn more about Lifted at Go-Lifted and follow on LinkedIn.
In this role, you will help shape the reinforcement learning systems that power high-impact experiences across Upwork, including Search & Recommendations and Uma, our AI assistant.

Build scalable retrieval and decisioning architectures that combine structured and unstructured data, including vector search, knowledge graphs, and retrieval-augmented generation workflows.
Lead cross-functional efforts to move ML and RL models from research prototypes into reliable production systems with strong performance, robustness, and observability.
Deliver high-impact outcomes aligned with organizational goals, while helping create clarity, structure, and momentum across complex cross-functional initiatives.
Track record of leading technically complex initiatives across research and engineering partners, with the judgment to balance experimentation, scalability, and production reliability.
This position will initially be employed through a partner to ensure a seamless hiring process while we establish the hub.
Upwork is committed to building a diverse, inclusive, and equitable workforce.

The annual base salary range for this position is displayed below.
The range displayed reflects the minimum and maximum salary for this position, and individual base pay will depend on your skills, qualifications, experience, and location.

Proven experience designing, training, and deploying reinforcement learning systems in production, with deep familiarity in planning methods such as Monte Carlo Tree Search and policy or value-based approaches.
Strong expertise in machine learning systems that use vector databases, graph databases, knowledge graphs, or graph neural networks to improve reasoning and decision quality.
Passion for building intelligent agent systems that combine reinforcement learning, large language models, and retrieval techniques to solve meaningful product and platform challenges.
Design and advance reinforcement learning systems for reasoning and planning, including approaches inspired by Monte Carlo Tree Search, policy and value networks, and modern agentic decision-making methods.
Partner closely with engineering, research, and Trust & Safety teams to improve explainability, interpretability, and risk mitigation across reinforcement learning and agent-based systems.
Evaluate emerging techniques in reinforcement learning, planning, and LLM-enabled systems, and translate promising innovations into practical applications for Upwork's platform.
Our partner will offer competitive benefits.
When Upwork's hub is established, we will be excited to offer employment and benefits directly as business needs require.
Employment decisions are made without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, disability, or any other status protected by applicable law.

While employed by the partner, you'll work as part of Upwork's team, with access to our resources, culture, and growth opportunities.

Candidates who prefer not to have their interview recorded through BrightHire can opt out when the interview is scheduled.

This listing is sourced directly from Upwork's careers page and normalized into a canonical job model.