About the Role
We are actively seeking individuals who excel in problem-solving and critical thinking, are proficient in coding, with proven track records of learning and growth, and have prior experience in ML model, feature, and infrastructure development.
What you'll do:
- 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.
- Define success metrics and develop dashboards to monitor and visualize the performance of ML models in production.
- Work closely with cross-functional teams, including Product, Engineering, and Data Science, to translate business requirements into ML solutions.
- Mentor and provide technical guidance to junior ML engineers and data scientists.
- Stay up-to-date with the latest research and advancements in machine learning, recommendation systems, and ad auction techniques.
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What you'll need:
- 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.
- 8+ years of industry experience as an ML engineer or equivalent.
- Experience with enabling production-scale and maintaining large ML models.
- Experience in one or more object-oriented programming languages (e.g. Python, Go, Java, C++) and one ML framework (Pytorch, Tensorflow)
- Experience with state-of-the-art deep learning techniques.
- Advanced degree (Ph.D. or M.S.) in Data Science, ML, or related disciplines.
We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have the curiosity, passion, and collaborative spirit, work with us, and let's move the world forward, together.
Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.
*Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to accommodations@uber.com.