Staff Machine Learning Engineer, Rider Pricing & Incentives

Uber

Hybrid

Quick summary

Work type: Hybrid
Location: Sunnyvale, CA
Salary: $232,000–$232,000 / yr
Posted: 24 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $227k

This role $232k

$171k most similar roles pay here $275k

This role pays more than 57% of similar roles. Most pay $195,000–$259,212 — the shaded band above. At the midpoint, this role pays about $232k versus about $227k for comparable roles.

Based on 240 similar postings.

Employer

About Uber

Uber Technologies, Inc. is the world’s largest, San Francisco-based mobile technology platform facilitating on-demand ride-hailing, food delivery (Uber Eats), and freight transportation across approximately 70 countries.

Uber currently has 95 open roles on FindRole.

Listed pay typically runs $232,000–$232,000 across 76 roles with salary data.

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At a glance

TL;DR · Staff Machine Learning Engineer, Rider Pricing & Incentives

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As a Staff Machine Learning Engineer on Uber’s Rider Pricing & Incentives team, you will lead a group of software engineers and machine learning experts to develop advanced pricing algorithms and promotional systems that optimize rider experiences globally. Your daily tasks include enhancing the performance of models and algorithms, collaborating with cross-functional teams to define technical roadmaps, and mentoring junior members in ML best practices. You’ll work extensively with deep learning, generative AI for personalized communications, causal modeling, and reinforcement learning to drive Uber’s ridership and revenue growth. The role requires proficiency in programming languages like Python or Java, experience with machine learning and optimization algorithms, and familiarity with large-scale data systems such as Spark and Hive.

Skills

Python Java Go Spark Hive Deep Learning Generative AI Causal Modeling Reinforcement Learning CI/CD MLOps

What you'll do

Lead the development of new machine learning techniques for rider pricing and promotions.
Improve performance of models and algorithms used in pricing strategies and promotion targeting.
Define technical roadmaps and work with cross-functional teams to align on goals.
Mentor junior team members by demonstrating best practices in machine learning.
Design and evolve systems to support new product and algorithm evolutions.

What we're looking for

Master’s degree in Computer Science, Engineering, Mathematics or related field with 7+ years of full-time engineering experience.
Proficiency in programming languages such as C, C++, Java, Python, Go.
Experience with machine learning and optimization algorithms.
Ability to translate complex business problems into ML and optimization solutions.
Familiarity with large-scale data systems like Spark, Hive, and building production-ready algorithmic systems.
Strong background in deep learning, generative AI, causal modeling, and reinforcement learning.

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