Machine Learning Engineer II, Pricing

Reposted 21 Days Ago
4 Locations
In-Office
171K-190K Annually
Junior
Logistics • Transportation • 3PL: Third Party Logistics
We reimagine the way the world moves for the better.
The Role
Design, develop, and productionize machine learning models and pricing algorithms for Uber’s large-scale, real-time marketplace systems. The role focuses on deep learning, causal modeling, reinforcement learning, optimization, and online serving at high volume. Responsibilities include collaborating with engineers, product managers, and scientists, shaping technical direction, solving complex marketplace problems, mentoring junior engineers, and monitoring ML solutions across offline and online environments.
Summary Generated by Built In

About the Role

Uber’s Marketplace is at the heart of Uber’s business and the Dynamic Supply Pricing (DSP) team develops the models, algorithms, signals, and large-scale distributed systems that power real-time driver pricing for billions of rides. Engineers on the team work on cutting-edge marketplace ML problems and real-time multi-objective optimizations serving 1M+ predictions/second. They regularly present $1B+ opportunities to executive stakeholders and receive close mentorship from the most senior engineers within the organization, setting you up for fast-tracked career growth and the opportunity to learn from experienced technical leaders.

 

We are looking for exceptional ML engineers with a track record of extraordinary impact and with a passion for building large-scale systems that optimize multi-sided real-time marketplaces. In this role, you will lead the design, development, and productionization of advanced ML models and pricing algorithms, covering deep learning, causal modeling, and reinforcement learning. You will work with engineers, product managers, and scientists to set the team’s technical direction and solve some of Uber’s most challenging and most complex business problems in order to provide earnings opportunities for millions of drivers worldwide. 

 

What You Will Do

  • Design, develop, and productionize end-to-end ML solutions for large-scale distributed systems serving billions of trips
  • Develop novel pricing approaches for online marketplaces combining machine learning, algorithmic game theory, and optimization to provide earnings opportunities for millions of drivers
  • Partner with senior engineers to plan the scope and execution of projects and mentor junior team members on design and implementation
  • Work with a team of engineers, product managers, and scientists to design and deliver high-impact technical solutions to complex business problems

Basic Qualifications

  • Ph.D., M.S. or Bachelor's degree in Computer Science, Machine Learning, or Operations Research, or equivalent technical background with exceptional demonstrated impact
  • 2+ years of experience in developing and deploying machine learning models and optimization algorithms in large-scale production environments
  • Proficiency in programming languages such as Python, Scala, Java, or Go
  • Experience with large-scale data systems (e.g. Spark, Ray), real-time processing (e.g. Flink), and microservices architectures
  • Experience in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps
  • Familiarity with modern ML algorithms (e.g. DNNs, multi-task models, transformers) and mathematical optimization (e.g. LP, convex optimization), combined with proven ability and ambition to continuously deepen expertise in these areas

Preferred Qualifications

  • Experience in translating ambiguous business problems into technical solutions in a structured and principled way
  • Strong communication skills, including through documentation and design discussions
  • Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior
  • Experience in reinforcement learning and causal machine learning

Responsibilities

For New York City, NY-based roles: The base salary range for this role is USD $171,000 per year - USD $190,000 per year.


For San Francisco, CA-based roles: The base salary range for this role is USD $171,000 per year - USD $190,000 per year.


For Seattle, WA-based roles: The base salary range for this role is USD $171,000 per year - USD $190,000 per year.


For Sunnyvale, CA-based roles: The base salary range for this role is USD $171,000 per year - USD $190,000 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.

About Us

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.

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.

Skills Required

  • Ph.D., M.S., or bachelor's degree in Computer Science, Machine Learning, Operations Research, or equivalent technical background with exceptional demonstrated impact
  • At least 2 years of experience developing and deploying machine learning models and optimization algorithms in large-scale production environments
  • Proficiency in Python, Scala, Java, or Go
  • Experience with large-scale data systems such as Spark or Ray
  • Experience with real-time processing systems such as Flink
  • Experience with microservices architectures
  • Experience developing, training, productionizing, and monitoring machine learning solutions at scale, including offline pipelines, online serving, and MLOps
  • Familiarity with modern machine learning algorithms, including deep neural networks, multi-task models, or transformers
  • Familiarity with mathematical optimization, including linear programming or convex optimization
  • Experience translating ambiguous business problems into structured technical solutions
  • Strong communication skills, including documentation and design discussions
  • Experience developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior
  • Experience in reinforcement learning and causal machine learning

Uber Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Uber and has not been reviewed or approved by Uber.

  • Parental & Family Support — Policies provide a minimum of fully paid parental leave for all parents and financial support for fertility, adoption, and surrogacy, with added credits to ease the transition. Programs extend to family medical leave and parenting support resources, indicating depth beyond baseline offerings.
  • Healthcare Strength — Healthcare coverage is described as comprehensive across many countries, with medical, dental, vision, life, disability, and mental health benefits, plus allowances where direct plans are not available. Wellness programs and reimbursements further reinforce access to care.
  • Wellbeing & Lifestyle Benefits — Monthly ride and meal credits, free office meals/snacks, fitness stipends, onsite gyms, and wellbeing reimbursements create meaningful everyday value. Home‑office stipends, travel medical coverage, and counseling support round out lifestyle-oriented perks.

Uber Insights

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The Company
HQ: San Francisco, CA
21,000 Employees
Year Founded: 2009

What We Do

We are Uber. The go-getters. The kind of people who are relentless about our mission to help people go anywhere and get anything. Movement is what we do. It’s our lifeblood. It runs through our veins. It’s what gets us out of bed each morning. It pushes us to constantly reimagine how we can move better. For you. For all the places you want to go. For all the things you want to get. For all the ways you want to earn. Across the entire world. In real-time. At the incredible speed of now.

Why Work With Us

We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have the curiosity, passion, and collaborative spirit, work with us, and let’s move the world forward, together.

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