About the Role
We are looking for a Machine Learning Scientist to join our Michelangelo ML Platform team. In this role, you will be able to use your skills in the fields of Machine Learning, Statistics, Generative AI to meaningfully improve our engineering platform.
Example projects we work on include: automatic incident leveling, compute allocation optimization, activity recognition on mobile.
The Michelangelo team works on building end-to-end ML systems and up-leveling ML quality at Uber. You will be part of a team of strong software and systems engineers, performing in a fast-paced environment. For more information on the Michelangelo Machine Learning Platform, see our select blog posts:
https://www.uber.com/en-NL/blog/from-predictive-to-generative-ai
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https://www.uber.com/en-NL/blog/scaling-ai-ml-infrastructure-at-uber
What the Candidate Will Do
- Design, build, deploy machine learning, generative ai, optimization models into Uber production systems for a wide range of applications.
- Collaborate with multi-functional teams across areas such as product, engineering, operations, and design to drive system development end-to-end from conceptualisation to productionisation.
- Understanding product performance and to find opportunities within data.
- Present findings to senior management to influence business decisions.
Basic Qualifications
- 5+ years of proven experience as a Machine Learning Scientist, Machine Learning Engineer, Software Engineer or equivalent.
- Experience in production coding and deploying ML, statistical, optimization models in real-time systems.
- Ability to use Python or other programming languages to work efficiently at scale with large data sets in production systems.
- Thought leadership to drive multi-functional projects from conceptualisation to productionisation.
- M.S., or Bachelors degree in Computer Science, Machine Learning, Statistics, Economics, Operations Research, or other quantitative fields.
Preferred Qualifications
- Experience working on ML Platforms
- Strong software engineering skills
- Experienced production user of ML frameworks such as XGBoost, Ray, Tensorflow, PyTorch, Keras, Spark etc.
- Familiarity with recent LLM advancements
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.