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$200,550–$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, you will join the engineering team to architect and build scalable systems that maintain an efficient and reliable marketplace. You will be responsible for developing and optimizing machine learning models to enhance delivery marketplace efficiency while designing long-lasting artifacts to increase developer velocity across the organization. Your daily work involves solving complex problems at the intersection of low latency and high correctness, translating ambiguous business requirements into technical roadmaps, and mentoring other engineers. The role requires expertise in SQL, data warehousing, and deep-learning techniques. You will utilize tools such as Flink, Spark, Apache Pinot, Druid, and the Hadoop ecosystem to manage large-scale distributed systems. This position focuses on solving high-impact problems within a global marketplace where performance and reliability are critical for millions of users.
What does a Machine Learning Engineer earn in California?
Median $247075 from 166 postings across 28 companies.
Develop and optimize machine learning models to improve the efficiency of the delivery marketplace.
Design and build engineering artifacts that reduce system complexity and increase developer velocity.
Solve high-impact problems involving low latency and high correctness in large-scale systems.
Translate ambiguous business requirements from cross-functional partners into production-ready technical roadmaps.
Lead the development and adoption of organization-wide frameworks and coding best practices.
Identify architectural gaps and proactively address potential issues before they impact the global marketplace.
Mentor other engineers and serve as a technical brand ambassador for the engineering organization.
Oversee incident management processes and direct on-call rotations following global best practices.
What we're looking for
5+ years of professional experience in software engineering, data engineering, and applying machine learning, statistics, or optimization techniques to solve large-scale problems.
Expertise in writing high-quality code to solve strategically important problems across multiple organizations.
Advanced proficiency in SQL and data warehousing with the ability to identify and reconcile architectural gaps.
Experience leading organization-wide engineering projects through all lifecycle stages including inception, stakeholder engagement, implementation, and operations.
Proven track record of overseeing incident management processes and directing on-call rotations.
Bachelor’s or Master’s degree in Computer Science, Engineering, or equivalent practical experience.
Experience building high-performance, scalable distributed systems at a 100M+ user scale (preferred).
Experience designing scalable ML solutions using deep-learning techniques and statistical methods (preferred).
Machine Learning
Natural Language Processing
PyTorch
TensorFlow
JAX
Python
Go
Java
C++
Computer Vision
Deep Learning
Content Moderation
Adversarial Training
Search Ranking
Information Retrieval
Multimodal Content Filtering
Machine Learning
Natural Language Processing
PyTorch
TensorFlow
JAX
Python
Go
Java
C++
Computer Vision
Deep Learning
Search Ranking
Retrieval Pipelines
Adversarial Training
Content Moderation
Red-teaming
Machine Learning
Natural Language Processing
PyTorch
TensorFlow
JAX
Python
Go
Java
C++
Computer Vision
Deep Learning
Content Moderation
Adversarial Training
Search Ranking
Information Retrieval
Machine Learning
Natural Language Processing
PyTorch
TensorFlow
JAX
Python
Go
Java
C++
Computer Vision
Deep Learning
Content Moderation
Adversarial Training
Search Ranking
Information Retrieval
Multimodal Content Filtering