Director, Machine Learning

Upwork•Chicago, TX

23h•Remote

About The Position

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, which connects businesses with on-demand access to highly skilled talent across the globe, and Lifted, which provides a purpose-built solution for enterprise organizations to source, contract, manage, and pay talent across the full spectrum of contingent work. From Fortune 100 enterprises to entrepreneurs, businesses rely on Upwork Inc. to find and hire expert talent, leverage AI-powered work solutions, and drive business transformation. With access to professionals spanning more than 10,000 skills across AI & machine learning, software development, sales & marketing, customer support, finance & accounting, and more, the Upwork family of companies enables businesses of all sizes to scale, innovate, and transform their workforces for the age of AI and beyond. Since its founding, Upwork Inc. has facilitated more than $30 billion in total transactions and services as it fulfills its purpose to create opportunity in every era of work. 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 . Search & Recommendations sits at the center of how work happens on Upwork. In this role, you will lead the engineering organization responsible for building the systems that connect millions of clients and freelancers across the globe. You will shape the future of Upwork’s matching platform by setting technical direction, scaling core systems, and delivering experiences that power everything from search and browse to conversational matching, agentic workflows, and emerging AI-native surfaces. This is a high-impact leadership opportunity to guide a strong engineering team while partnering closely with product, machine learning, and executive leadership on a platform central to Upwork’s long-term growth.

Requirements

Significant experience leading engineering teams in high-scale environments, with a strong track record of delivering search, recommendations, ranking, or retrieval systems that drive meaningful business results.
Deep technical fluency in distributed systems, data pipelines, search architecture, and modern machine learning infrastructure, with the ability to guide architecture decisions and mentor senior engineers and managers.
Proven success leading integrated teams of software engineers and machine learning engineers while building strong partnerships across product, data science, and executive stakeholders.
Ability to operate effectively at multiple altitudes, translating technical depth into strategic clarity and making sound decisions in ambiguous, fast-moving environments.
Strong applied understanding of AI-native engineering workflows, including using AI to accelerate design, experimentation, and delivery while ensuring technical accuracy, responsible use, and scalable team adoption.

Responsibilities

Define and drive the technical strategy for Upwork’s Search & Recommendations platform, aligning engineering investments with long-term business goals, marketplace performance, and platform scalability.
Lead, grow, and develop a high-performing organization of software and machine learning engineers, fostering a culture of ownership, inclusion, high standards, and continuous learning.
Deliver a unified Search & Recommendations platform that powers matching experiences across client and talent journeys, including search, recommendations, conversational experiences, and agentic workflows.
Modernize search infrastructure by guiding the migration from legacy systems to scalable, maintainable, and high-performance architectures with clear APIs, observable pipelines, and strong experimentation support.
Partner closely with product, ML, data science, design, and senior leadership to prioritize roadmaps, navigate tradeoffs, and translate complex platform decisions into measurable business outcomes.
Champion engineering excellence through strong practices in system reliability, latency, data integrity, responsible AI development, and operational health across critical marketplace systems.
Establish clear operating mechanisms, metrics, and team rhythms that improve execution, support long-range planning, and track platform health, engineering effectiveness, and business impact.