below marketmost similar roles pay hereabove market
This listing doesn't post a salary. Most similar roles pay
$197,750–$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 Senior Machine Learning Engineer - Pricing joins the Dynamic Supply Pricing team to develop models, algorithms, and large-scale distributed systems for real-time driver pricing. In this role, you will lead the design, development, and productionization of end-to-end machine learning solutions and pricing algorithms for multi-sided real-time marketplaces. You will collaborate with engineers, product managers, and scientists to solve complex business problems and provide earnings opportunities for millions of drivers. Key responsibilities include setting technical direction and mentoring junior engineers. Required skills include proficiency in Python, Scala, Java, or Go, along with experience in Spark, Ray, Flink, and microservices. You must demonstrate expertise in deep learning, transformers, multi-task models, causal modeling, reinforcement learning, and mathematical optimization techniques like linear programming and convex optimization.
What does a Machine Learning Engineer earn in New York?
Median $231150 from 51 postings across 20 companies.
Lead the design, development, and productionization of end-to-end ML solutions for large-scale distributed systems.
Develop novel pricing approaches combining machine learning, algorithmic game theory, and optimization for online marketplaces.
Set the team’s technical direction and own the implementation of complex technical projects.
Provide technical mentorship to junior engineers within the organization.
Design and deliver high-impact technical solutions to solve complex business problems.
Train, productionize, and monitor ML solutions ranging from offline pipelines to online serving and MLOps.
Translate ambiguous business problems into technical solutions and drive multi-functional projects.
What we're looking for
Ph.D., M.S. or Bachelor's degree in Computer Science, Machine Learning, or Operations Research, or equivalent technical background.
4+ years of experience developing and deploying machine learning models and optimization algorithms in large-scale production environments.
Proficiency in programming languages such as Python, Scala, Java, or Go.
Experience with large-scale data systems (e.g. Spark, Ray), real-time processing (e.g. Flink), and microservices architectures.
Experience in the development, training, productionization, and monitoring of ML solutions at scale 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. LP, convex optimization).
Experience in developing and deploying pricing algorithms for multi-sided real-time marketplaces with strategic agent behavior (preferred).
Experience in reinforcement learning and causal machine learning (preferred).
Machine Learning
Deep Learning
Generative AI
Optimization Algorithms
Python
C++
Java
Go
C
Spark
Hive
Causal Modeling
Reinforcement Learning
Representation Learning
Large-scale Data Systems
Production-ready Algorithmic Systems
Machine Learning
Deep Learning
Generative AI
Optimization Algorithms
Python
C++
Java
Go
C
Spark
Hive
Causal Modeling
Reinforcement Learning
Representation Learning
Large-scale Data Systems
Production-ready Algorithmic Systems