below marketmost similar roles pay hereabove market
This listing doesn't post a salary. Most similar roles pay
$202,800–$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.
The Sr Machine Learning Engineer- Maps Optimization joins the Maps Optimization team to build and maintain the foundational stack for location search, ETA calculation, and routing. This senior role involves designing, building, and optimizing large-scale machine learning systems and models to improve travel experience and logistical efficiency. You will develop and deploy end-to-end machine learning models and infrastructure, while maintaining high-throughput, low-latency prediction systems and APIs. The role requires expertise in machine learning, artificial intelligence, optimization, signal processing, and operational research. You will utilize technologies including Apache Spark, Hive, Presto, and Michelangelo, along with programming languages such as Java, Scala, Golang, and Python. The work focuses on solving complex machine learning challenges like graph prediction and learning to rank within a high-throughput production environment.
What does a Machine Learning Engineer earn in California?
Median $235750 from 200 postings across 34 companies.
Develop and deploy end-to-end machine learning models and infrastructure to optimize map-related applications.
Design and maintain high-throughput, low-latency prediction systems and APIs handling hundreds of billions of daily requests.
Build and optimize large-scale ML systems to improve efficiency and travel experience for millions of daily trips.
Develop, debug, and scale distributed data processing and ML pipelines using tools like Spark, Hive, and Presto.
Explore novel ideas to improve logistical efficiency across various product verticals.
Define and set the technical direction for complex machine learning projects.
Productionize applied machine learning solutions such as graph prediction and learning to rank.
What we're looking for
5+ years of experience in machine learning, or 2+ years if you have a PhD.
2+ years of experience in machine learning, AI, optimization, signal processing, operational research, or related technical fields.
Experience developing, debugging, and scaling distributed data processing and ML pipelines using tools like Apache Spark, Hive, Presto, or Michelangelo.
Knowledge of development and debugging in Java, Scala, or Golang, plus experience with Python and/or shell scripts.
Experience in technical leadership, including owning projects and defining technical direction.
Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
Experience architecting large scale, production software applications (preferred).
Python
C++
Machine Learning
Computer Vision
Geospatial Data
PostGIS
GeoPandas
GDAL/OGR
S2
H3
GeoJSON
SLAM
Point Cloud Processing
Graph Algorithms
3D Geometry