Machine Learning Engineer – Membership Engagement
Location: San Francisco, CA / Sunnyvale, CA / Hybrid or Office-based
About the Role
Uber has grown from a ride-hailing app into a platform offering a wide range of on-demand services. The Uber One Membership team empowers over 30 million members with exclusive benefits like best price, selection, priority, and perks—all in one place.
We’re looking for a Machine Learning Engineer to join the Membership Engagement organization. You’ll collaborate with top engineers, data scientists, and product leaders to develop cutting-edge optimization and personalization systems. Your work will directly influence Uber’s most strategic challenges and make a global impact.
What You Will Do
- Design and build Machine Learning models for large-scale personalization and optimization.
- Develop high-throughput systems processing millions of data points per minute and serving hundreds of thousands of QPS.
- Collaborate cross-functionally to identify new modeling opportunities and drive experimentation and product iteration.
- Write clean, scalable, and tested code across services and infrastructure.
- Lead solution design and tradeoff discussions around ambiguous technical challenges.
- Contribute to engineering excellence in reliability, monitoring, testing, and on-call processes.
Basic Qualifications
- Bachelor’s degree or equivalent in Computer Science, Engineering, Math, or related field.
- 2+ years of full-time engineering experience.
- 1+ year of experience developing, training, deploying, and monitoring ML optimization solutions at scale.
- Proficiency in big data tools (e.g., Hive, Kafka, Cassandra), ETL pipelines, and SQL.
- Strong programming skills in one or more languages (e.g., Python, Go, Java, C++).
- Demonstrated ability to work with cross-functional teams and deliver results.
- Fast learner with a go-getter attitude and willingness to step outside of your comfort zone.
Preferred Qualifications
- Experience translating business problems into ML/optimization formulations with measurable outcomes.
- Understanding of system design and architecture of ML workflows.
- Familiarity with deep learning, causal inference, personalization, and ranking models.
- Knowledge of optimization methods such as reinforcement learning, Bayesian methods, or multi-armed bandits.
- Experience tuning Spark jobs for performance and resource efficiency.
- Ownership of end-to-end, technically complex, multi-quarter engineering projects.
Compensation
San Francisco & Sunnyvale, CA: Base salary range is $167,000 – $185,500 per year.
All U.S. roles include eligibility for Uber’s bonus program, equity awards, and comprehensive benefits. For full details, visit: www.uber.com/careers/benefits
Why Join Uber?
- Make a real-world impact at a global scale
- Work on cutting-edge optimization and ML systems
- Collaborate with diverse and talented teams
- Be part of a company redefining on-demand services
Inclusion & Equal Opportunity
Uber is proud to be an Equal Opportunity Employer. We do not discriminate based on sex, gender identity, race, religion, age, disability, veteran status, or any other protected characteristic. We also consider applicants regardless of criminal histories, consistent with legal requirements.
If you have a disability or special need requiring accommodation, please let us know by completing this form.
Work Model
Uber values in-office collaboration. Unless formally approved for remote work, employees are expected to spend at least 50% of their time in-office. Certain roles may require full-time in-office presence.
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