Staff Machine Learning Engineer - Rider Intelligence

Uber’s Rider Intelligence team builds personalization that helps people find the right services from Uber’s app homepage at the right time. In this Staff Machine Learning Engineer role, you will shape the technical and scientific direction for homepage personalization and recommendation, with a focus on sequential recommendation, intent-aware ranking, and LLM-based and agentic approaches that extend beyond traditional retrieval and ranking.

Working onsite in Seattle, you will partner with product teams to turn modeling decisions into measurable improvements in user experience, engagement, and business outcomes across Uber’s business lines, while mentoring ML engineers and influencing technical direction across teams.

What you’ll do

• Drive ML technical strategy: Shape the technical and scientific direction for homepage personalization and recommendation systems.
• Build advanced ML solutions: Lead development of sequential recommendation models, intent-aware ranking, and LLM-based and agentic solutions.
• Deliver product impact: Partner with cross-functional teams to improve user experience, engagement, and business outcomes across Uber’s business lines.
• Provide technical leadership: Drive engineering excellence, influence technical decisions across teams, and mentor ML engineers.

Role context: Rider Intelligence

• The Rider Intelligence team powers personalization across Uber’s app homepage, supporting discovery of relevant services.
• Work includes ranking homepage components, predicting and suggesting users’ next destinations, understanding user intent to tailor experiences, presenting promotions at the right time, and optimizing the overall homepage experience across multiple business lines, including Rides, Eats, Grocery, and more.
• As Staff Machine Learning Engineer, you will guide the design and development of real-time sequential recommendation models, intent-aware ranking, and LLM-based and agentic solutions across these domains.

Requirements

• Deep expertise in machine learning, deep learning, and recommendation systems, including ranking, sequential modeling, and transformer architectures.
• Strong programming skills in Python3, with hands-on experience using PyTorch or TensorFlow.
• Proven track record leading complex ML initiatives, delivering measurable business impact, and influencing technical direction across teams.

About your background

• Experience: 8+ years of industry experience designing, developing, and deploying machine learning models in large-scale production environments.
• Education: Master’s or PhD degree in Computer Science, Machine Learning, or a related field.
• Advanced recommendation experience: Experience with transformer-based sequential modeling, generative recommendation, and foundation models for personalization.
• LLM/agentic application: Experience applying LLMs and agentic AI to personalization, recommendation, or user intent understanding.
• Ranking optimization: Experience optimizing multi-objective ranking systems across engagement, conversion, revenue, and long-term user value.
• Research impact: Demonstrated research contributions through publications at top-tier ML conferences, patents, or successful application of novel ML techniques in production.

Technologies

• Python3
• PyTorch
• TensorFlow

Compensation and location

• Location: Seattle, WA (onsite)
• Salary: USD 232,000 - 258,000 per year

Benefits

• Eligible to participate in Uber’s bonus program
• May be offered an equity award and other types of comp
• 401(k) plan eligibility
• Various benefits

Uber offices remain a key part of collaboration. Unless approved for full remote work, employees must spend at least 50% of their time in-office. For full details on any additional in-office requirements, ask your Recruiter for guidance specific to this role.