ABOUT THE TEAM
The Applied AI team collaborates with product teams across Uber to deliver innovative AI solutions for core business problems. We work closely with engineering, product and data science teams to understand core business problems and the potential for AI solutions, then deliver those AI solutions end-to-end. Key areas of expertise include Computer Vision, ML Optimization, Geospatial AI, Personalization and Generative AI.
The ML Optimization team within Applied AI is building new experiences to surface earnings opportunities on the Uber platform, particularly for new earners. We are looking for a strong Machine Learning Engineer to join our team in Amsterdam!
ABOUT THE ROLE
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Our team engages with partners across teams to design, develop and productionize machine learning systems for highly complex and vaguely defined problems.
WHAT YOU'LL DO
- Collaborate with product teams to analyze key business problems and develop innovative ML solutions.
- Collaborate with data science and engineering teams to integrate and validate ML solutions end-to-end.
- Deliver enduring value in the form of software and model artifacts.
BASIC QUALIFICATIONS
- Master or PhD or equivalent experience in Computer Science, Engineering, Mathematics or a related field and 2 years of Software Engineering work experience, or 5 years Software Engineering work experience.
- Experience in programming with a language such as Python, C, C++, Java, or Go.
- Experience with ML packages such as Tensorflow, PyTorch, JAX, and Scikit-Learn.
- Experience with SQL and database systems such as Hive, Kafka, and Cassandra.
- Experience in the development, training, productionization and monitoring of ML solutions at scale.
PREFERRED QUALIFICATIONS
- Experience in modern deep learning architectures and probabilistic models.
- Experience in modern generative AI, such as transformer architectures, diffusion models and prompting.
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.