Software Engineer II - Machine Learning

Uber is seeking a Software Engineer II - Machine Learning to join their team in building machine learning solutions for all risk and fraud applications. This role offers the opportunity to work across all levels of Uber's ML stack, from infrastructure to ML model development and productionization.

Key responsibilities include:

1. Developing and productionizing machine learning algorithms for Uber's risk and fraud problems.
2. Performing data analysis to understand and drive product insights, further model iterations.
3. Continuously innovating and applying state-of-the-art ML algorithms at Uber Scale.
4. Establishing best practices and improving the rigor and bar of Applied ML.

The ideal candidate will have:

• A Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or a related field, with some software engineering experience gained through industry work.
• Proficiency in one or more object-oriented programming languages such as Python, Go, Java, C++.
• Experience with big-data architecture, ETL frameworks, and platforms (e.g., Hive, Spark, Presto).
• Working knowledge of contemporary machine learning and deep learning frameworks (e.g. PyTorch, TensorFlow, JAX).

Preferred qualifications include:

• Deep understanding of all aspects of machine learning model lifecycles.
• Experience with cutting-edge machine learning research.
• Experience building applications with large language models.
• Strong statistical and experimental foundation to develop insights from data.

The base salary range for this role in Sunnyvale, CA is $158,000 - $175,500 per year, with additional benefits and equity opportunities available. Uber is committed to equal employment opportunity and values diversity in its workforce.