Staff Machine Learning Engineer - Rider Intelligence

Shape personalization and recommendation experiences at scale. Uber’s Rider Intelligence team is building the systems behind what riders see on the app homepage and how suggestions are timed to user intent. As a Staff Machine Learning Engineer in Seattle (onsite), you’ll influence the technical and scientific direction of homepage ranking and sequential recommendation, while leading modern approaches including LLM and agentic solutions.

What you’ll do

• Set ML technical strategy to define the technical and scientific direction for homepage personalization and recommendation systems.
• Lead advanced model development for sequential recommendation, intent-aware ranking, and LLM-based and agentic solutions.
• Drive measurable product impact by partnering with cross-functional teams to improve user experience, engagement, and business outcomes across Uber’s business lines.
• Provide technical leadership by guiding engineering excellence, influencing technical decisions across teams, and mentoring ML engineers.

How the Rider Intelligence team works

The Rider Intelligence team powers personalization across Uber’s app homepage. You’ll work across areas such as ranking homepage components, predicting and suggesting users’ next destinations, understanding user intent for tailored experiences, presenting promotions at the right time, and optimizing the homepage across multiple business lines including Rides, Eats, Grocery, and more.

In this role, you’ll lead the design and development of real-time ML solutions that move beyond traditional retrieval and ranking. You’ll also partner closely with product teams to deliver personalized experiences, set technical direction across teams, and strengthen technical excellence through mentoring.

Required qualifications

• 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, driving measurable business impact, and influencing technical direction across teams.

Preferred qualifications

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

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

Role logistics

Offices remain key to collaboration at Uber. Unless approved for full remote work, employees must spend at least 50% of their time in-office.

Minimum experience and education

• Minimum experience: 8 years
• Education: Master’s or PhD degree in Computer Science, Machine Learning, or a related field

Technologies

• Python3
• PyTorch
• TensorFlow