Machine Learning Engineer II
Description For Machine Learning Engineer II
Uber is seeking a Machine Learning Engineer II to join our team. In this role, you will be at the forefront of optimizing our ad recommendations and auction mechanisms through advanced machine learning techniques. You'll design and implement ML models, apply statistical methods to improve ad targeting, and ensure the reliability of our predictions at scale.
We're looking for candidates with a strong background in computer science, data science, or related fields, with proven experience in implementing ML models in production environments. Proficiency in Python and experience with large-scale data processing technologies like Spark are essential.
As part of the Uber team, you'll work in a dynamic, fast-paced environment where innovation is key. You'll have the opportunity to stay current with the latest advancements in machine learning and ad tech, applying cutting-edge techniques to real-world problems.
We offer a competitive salary range of $158,000 to $175,500 per year, along with opportunities for bonuses, equity awards, and comprehensive benefits. Our offices are central to our collaborative culture, and we expect employees to spend at least half of their work time in their assigned office.
Join us in shaping the future of technology-driven transportation and delivery services. At Uber, you'll be part of a team that's revolutionizing the way people move, work, and live in cities around the world.
Responsibilities For Machine Learning Engineer II
- 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 For Machine Learning Engineer II
- 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
