below marketmost similar roles pay hereabove market
This listing doesn't post a salary. Most similar roles pay
$196,512–$254,750.
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.
As a Sr Machine Learning Engineer on the Pricing & Incentives team, you will build innovative products and scalable systems that power a global marketplace. You will design machine learning models to jointly optimize demand levers, including TDF, TSF, HVAs, and EUP, to improve marketplace efficiency by modeling coordination across pricing and incentive levers. Your daily responsibilities include owning the software lifecycle from design docs to production rollout, debugging live issues, and managing incidents. You will collaborate with Product, Applied Science, and Ops teams to translate ambiguous marketplace problems into robust system designs. Required skills include proficiency in Go, Java, or Python, along with experience in statistics, optimization techniques, distributed systems, and large-scale data processing. You should also understand high-throughput, low-latency services and real-time data streaming tools like Kafka or Flink.
What does a Machine Learning Engineer earn in California?
Median $231150 from 187 postings across 27 companies.
Design machine learning models to jointly optimize demand levers like pricing and incentives.
Model the coordination across various marketplace levers to improve overall efficiency.
Own the full software lifecycle from initial design documents to production rollout.
Debug live production issues and manage system incidents.
Translate ambiguous marketplace problems into robust system designs.
Design and operate high-throughput, low-latency services.
Exercise sound judgment on engineering trade-offs with direct business impacts.
What we're looking for
5+ years of professional software engineering experience in ML, statistics, optimization techniques, distributed systems, or large-scale data processing.
Proficiency in one or more programming languages such as Go, Java, or Python.
Experience designing and operating high-throughput, low-latency services and translating business problems into system designs.
Bachelor's Degree or equivalent experience in Computer Science, Engineering, or a related technical field.
Experience with marketplace, pricing, dispatch, forecasting, or other real-time decision systems (preferred).
Familiarity with real-time data streaming (e.g., Kafka, Flink) or time-series forecasting pipelines (preferred).
Demonstrated ability to exercise sound judgment on engineering trade-offs where algorithm behavior has direct business impact (preferred).
Go
Java
Python
C++
Spark
Flink
Kafka
Distributed Systems
Data Engineering
Data Modeling
Query Optimization
System Design
Monitoring
Statistical Modeling
PyTorch
TensorFlow
JAX
Python
Go
Java
C++
Natural Language Processing
Deep Learning
Computer Vision
Machine Learning
Adversarial Training
Content Moderation
Search Ranking
Retrieval Pipelines
PyTorch
TensorFlow
JAX
Python
Go
Java
C++
Natural Language Processing
Deep Learning
Computer Vision
Machine Learning
Adversarial Training
Content Moderation
Search Ranking
Retrieval Pipelines
PyTorch
TensorFlow
JAX
Python
Go
Java
C++
Natural Language Processing
Deep Learning
Computer Vision
Machine Learning
Adversarial Training
Content Moderation
Search Ranking
Retrieval Pipelines