Machine Learning Engineer

$158,000 - $175,500/Yr

Uber - Sunnyvale, CA

Full-time - Mid Level

Remote - Sunnyvale, CA

Transit and Ground Passenger Transportation

About the position

The Machine Learning Engineer role at Uber focuses on managing pricing and marketplace balance through advanced machine learning techniques and economic modeling. The position involves designing and building machine learning models, deploying them for real-world applications, and collaborating with cross-functional teams to enhance product solutions. This role offers a unique opportunity to work at the intersection of machine learning and economics, leveraging rich data for high-quality simulations and policy optimizations.

Responsibilities

• Design and build Machine Learning models with optimization engines.
• Productionize and deploy these models for real-world application.
• Review code and designs of teammates, providing constructive feedback.
• Collaborate with Product and cross-functional teams to brainstorm new solutions and iterate on the product.

Requirements

• Bachelor's degree or equivalent in Computer Science, Engineering, Mathematics or related field, with 2+ years of full-time engineering experience or PhD new grad.
• Experience working with multiple multi-functional teams (product, science, product ops etc).
• Expertise in one or more object-oriented programming languages (e.g. Python, Go, Java, C++).

Nice-to-haves

• 1+ year of ML/economics experience and building ML/economic models.
• Experience with the design and architecture of ML systems and workflows.
• Experience with building algorithmic solutions in production, making practical tradeoffs among algorithm sophistication, compute complexity, maintainability, and extensibility in production environments.
• Experience with taking on vague business problems, translating them into ML + Optimization formulation, identifying the right features, model structure and optimization constraints, and delivering business impact.
• Experience with optimizing Spark queries for better CPU and memory efficiency.
• Working knowledge of latest ML technologies, and libraries, such as PyTorch, TensorFlow, JAX, Ray, etc.
• Experience owning and delivering a technically challenging, multi-quarter project end to end.
• Experience with big-data architecture, ETL frameworks and platforms, such as HDFS, Hive, MapReduce, Spark, etc.

Benefits

• Participation in Uber's bonus program.
• Potential equity award and other types of compensation.
• Various benefits as detailed on Uber's careers benefits page.