Staff Machine Learning Engineer - Rider Intelligence

Lead ML engineering and scientific direction for Uber’s Rider Intelligence personalization and recommendation systems, focused on homepage experiences.

Responsibilities

• Set ML technical strategy for homepage personalization and recommendation systems
• Lead development of sequential recommendation models
• Build intent-aware ranking approaches to tailor user experiences
• Develop LLM-based and agentic solutions that extend beyond traditional retrieval and ranking
• Partner with cross-functional product teams to improve user experience, engagement, and business outcomes across Uber business lines
• Provide technical leadership by driving engineering excellence and influencing technical decisions across teams
• Mentor ML engineers and support development at multiple levels

What the Rider Intelligence team does

• Power personalization across Uber’s app homepage
• Support users in discovering and accessing relevant services at the right time
• Work across ranking homepage components, predicting and suggesting next destinations, and understanding user intent
• Help present promotions at appropriate moments and optimize the overall homepage experience
• Impact multiple business lines, including Rides, Eats, Grocery, and more

Requirements

• Deep expertise in machine learning, deep learning, and recommendation systems, including:
  • Ranking
  • Sequential modeling
  • Transformer architectures
• Strong Python3 programming skills, with hands-on experience using ML frameworks including PyTorch or TensorFlow
• Proven experience leading complex ML initiatives
• Experience driving measurable business impact and influencing technical direction across teams

Preferred qualifications

• 8+ years of industry experience designing, developing, and deploying ML 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, including:
  • Transformer-based sequential modeling
  • Generative recommendation
  • 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 production application of novel ML techniques

Technology

• Python3
• PyTorch
• TensorFlow

Compensation and benefits

• Base salary range: USD 232,000 - 258,000 per year (Seattle, WA)
• Eligible to participate in Uber’s bonus program
• May be offered an equity award and other types of compensation
• 401(k) plan eligibility
• Various benefits

Location and work model

• Seattle, WA (onsite)
• Offices remain key to collaboration; unless approved for full remote work, employees must spend at least 50% of time in-office
• Some roles may require full-time in-office presence; ask the Recruiter for details

Minimum experience: 8 years

Education: Master’s or PhD degree in Computer Science, Machine Learning, or a related field