Uber logo

Sr Machine Learning Engineer- Maps Optimization

Uber

Sunnyvale, CA · HybridFull-time$202–224K/yrSeen 3w agoSeen in employer's feed today

Most applications go out cold — see where you stand first. No sign-up to start.

You apply on the employer's site, with no Olive account needed.

Watch jobs like this.

Don't just apply. Show up ready.

Olive works from this exact posting.

At a glance

Compensation
$202–224K/yr
Location
Sunnyvale, CAHybrid
Schedule
Full-time
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Job overview

Uber’s Maps Optimization team builds the machine-learning systems behind map search, ETA calculation, and routing. The senior engineer will design and optimize large-scale models and infrastructure to improve efficiency and travel experiences across millions of trips. The role focuses on end-to-end model development, high-throughput prediction systems, and collaboration across product and engineering teams.

Skills & qualifications

RequiredNice to have

Skills

Machine LearningArtificial IntelligenceOptimizationSignal ProcessingOperational ResearchDistributed Data ProcessingML PipelinesApache SparkHivePrestoMichelangeloJavaScalaGolangPythonShell ScriptingTechnical LeadershipProject OwnershipTechnical DirectionProduction Software ArchitectureProductionizing Machine LearningGraph PredictionLearning to RankProduction ML SystemsEnd-to-End OwnershipAdaptabilityWorking in Ambiguity

Qualifications

5+ Years Machine Learning Experience or PhD With 2+ Years2+ Years Related Technical ExperienceBachelor's in Computer Science or Related Field or Equivalent ExperienceMaster's or PhD in Computer Science or Related Field

Benefits

401(k) Match

Full job description

About the Role

The Maps Optimization team builds and maintains the foundational stack powering the full user journey on the Uber map, including location search, ETA calculation and routing. Our technology leverages advanced machine learning models and high-throughput scalable infrastructure capable of serving millions of QPS. The work of the team influences Uber’s core business performance in a meaningful way and is highly visible to the executive leadership team.

We are looking for a highly motivated, entrepreneurial machine learning engineer to join the Maps Optimization team. As a senior machine learning engineer, you will design, build, and optimize large-scale ML systems and models to improve efficiency and travel experience across millions of daily trips worldwide.

Basic Qualifications

  • 5+ years of experience in the domain of machine learning, or 2+ years if you have a PhD

  • 2+ years of experience in one or more of the following areas: machine learning, artificial intelligence, optimization, signal processing, operational research, or related technical fields

  • Experience developing, debugging, and scaling distributed data processing and ML pipelines (e.g., Apache Spark, Hive, Presto, Michelangelo)

  • Knowledge of development and debugging in Java, Scala, or Golang, and experience with scripting languages such as Python and/or shell scripts

  • Experience in technical leadership, working with teams, owning projects, defining and setting technical direction for projects

  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

Preferred Qualifications

  • Experience architecting large scale, production software applications

  • Experience productionizing applied machine learning solutions (e.g., graph/graphless prediction, learning to rank) toward solving complex ML challenges

  • Masters degree or PhD in Computer Science or a related technical field

What the You Will Do

  • Develop and deploy end-to-end machine learning models and infrastructure to optimize Uber map related applications

  • Design and maintain high-throughput, low-latency prediction systems and APIs handling hundreds of billions of daily requests

  • Explore novel ideas towards improving Uber's logistical efficiency across its product verticals

  • Partner with product managers, scientists, designers, and engineers to develop holistic solutions to real world problems

You might thrive in this position if you:

  • Have extensive prior experience building and maintaining production machine learning systems

  • Own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done

  • Have the ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines

For San Francisco, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.

For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.

Ready to Ride?

This isn't the kind of place where you follow a playbook — it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves — we'd love to hear from you.

You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits. (https://jobs.uber.com/en/benefits/)

Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements.

Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form. (https://forms.gle/aDWTk9k6xtMU25Y5A?uclick\_id=d56eb634-bfb9-455e-a50d-901b3de0490c)

Uber is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form- https://docs.google.com/forms/d/e/1FAIpQLSdb_Y9Bv8-lWDMbpidF2GKXsxzNh11wUUVS7fM1znOfEJsVeA/viewform

How this job compares

Set against the 6,127 open Machine Learning Engineer jobs on Olive Jobs, counted November 6, 2026.

Pay
  • This posting$202–224K/yr
  • California median$177–262K/yr1,407 salary ranges
  • US median$150–245K/yr4,889 salary ranges

This range's midpoint, $213K, is 4% below the California median midpoint ($223K) — in the middle half of Machine Learning Engineer salary ranges in California.

Openings
Olive Jobs lists 1,880 open Machine Learning Engineer jobs in California and 6,127 across the US. 8% of them nationwide are listed as remote or flexible.
Hiring the most in California
Experience
This posting asks for at least 2 years of experience — less than three in four Machine Learning Engineer postings that state a minimum ask for (median 5 years, across 4,896 postings).
Education
2,195 of the 6,127 open Machine Learning Engineer jobs (36%) ask for a bachelor's degree or higher.

Counted across the open, public US postings on Olive Jobs on November 6, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.

Prepare for this role

You've read the whole posting — now see how you match it.