Machine Learning Engineer II

$158,000 - $175,500/Yr

Uber - New York, NY

Full-time - Mid Level

Remote - New York, NY

Transit and Ground Passenger Transportation

About the position

The Ads Machine Learning (Ads ML) team at Uber is focused on enhancing ad recommendations across various applications within the Uber ecosystem. This role involves defining and executing the Ads ML roadmap to drive large-scale improvements in recommendation systems, ultimately benefiting both users and merchants. The position is crucial for the growth of Uber's Ads Business strategy, emphasizing the development of robust and observable ad recommendations.

Responsibilities

• Design and implement machine learning models and algorithms to optimize ad recommendations and auction mechanisms.
• Apply advanced statistical and machine learning techniques to generate insights and improve the effectiveness of ad targeting and delivery.
• Monitor and ensure the reliability of ML Predictions at large scale.
• Stay up-to-date with the latest research and advancements in machine learning, recommendation systems, and ad auction techniques.

Requirements

• Bachelor's degree or equivalent experience in Computer Science, Computer Engineering, Data Science, ML, Statistics, or other quantitative fields.
• Proven experience with designing and implementing machine learning models in production environments applied to recommendation systems.
• Proficiency in using Python for developing ML models and handling large-scale data sets.
• Hands-on experience with building batch data pipelines using technologies like Spark or other map-reduce frameworks.

Nice-to-haves

• 2 years of industry experience as an ML engineer or equivalent.
• Experience with enabling production-scale and debugging large ML models.
• Experience in one or more object-oriented programming languages (e.g. Python, Go, Java, C++).
• Advanced degree (Ph.D. or M.S.) in Data Science, ML, or related disciplines.

Benefits

• Participation in Uber's bonus program
• Potential equity award
• Various benefits as detailed in the job description.