Postmates Jobs

Staff Machine Learning Engineer

• Marketplace Pricing

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

Drive technical strategy and roadmap ownership over a 1

• year horizon and own the implementation, including platform-level architecture decisions, executive communication and alignment, technical mentorship, and cross-team technical influence

Lead the design, development, and productionization of 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

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

6

• years experience leading the development and deployment of ML models and optimization algorithms in large-scale production environments at top-tier ML companies (e.g. 1M
• predictions/sec or 100M
• users). Track record of delivering outstanding business impact over multiple quarters

Proficiency in programming languages such as Python, Scala, Java, or Go

Proficiency with large-scale data systems (e.g. Spark, Ray), real-time processing (e.g. Flink), and microservices architectures

Proficiency in the development, training, productionization and monitoring of ML solutions at scale, ranging from offline pipelines to online serving and MLOps

Deep understanding of modern ML algorithms (e.g. DNNs, multi-task models, transformers) and mathematical optimization (e.g. multi-objective, LP, convex optimization)

Preferred Qualifications

Proficiency in reinforcement learning and causal machine learning

For New York, NY-based roles: The base salary range for this role is USD$223,000 per year

For San Francisco, CA-based roles: The base salary range for this role is USD$223,000 per year

For Seattle, WA-based roles: The base salary range for this role is USD$223,000 per year

For Sunnyvale, CA-based roles: The base salary range for this role is USD$223,000 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.

You will also be eligible for various benefits. More details can be found at the following link. Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.

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.

Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.