Director, Machine Learning - Search & Recommendation
New
U
UpworkTechnology/Marketplace
We currently hire full-time employees in 34 U.S. statesFull-TimeDirector
Salary$211,250 — $340,000 USD
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Job Details
- Required Skills
- Artificial IntelligenceMachine LearningDistributed Systems
Requirements
- Significant experience leading engineering teams in high-scale environments.
- 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.
- Ability to guide architecture decisions and mentor senior engineers and managers.
- Proven success leading integrated teams of software engineers and machine learning engineers.
- Strong partnerships across product, data science, and executive stakeholders.
- Ability to operate effectively at multiple altitudes, translating technical depth into strategic clarity.
- Applied understanding of AI-native engineering workflows, including using AI to accelerate design, experimentation, and delivery.
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.
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