Graduate 2024 Machine Learning Engineer I, San Francisco

Job Description

Posted on: 
June 4, 2024

Contributes to the design, development, optimization, and productionization of machine learning (ML) or ML-based solutions and systems that are used within a team to solve well-defined problems leveraging the support and guidance of others on the team. This role also learns to use and improve ML infrastructure for model development, training, deployment needs and scaling ML systems.


  • Develop and productionize machine learning algorithms for multiple business problems
  • Deeply engage with product datasets analyze them to understand and drive product insights, further model iterations.
  • Continuously innovate and apply state-of-the-art ML algorithms at Uber Scale.
  • Establish best practices and improve the rigor and bar of ML in Uber Eats

Job Requirements

Minimum Qualifications

Completing a Bachelor’s degree or equivalent in Computer Science, Engineering, Mathematics, or a related field, plus a 3-months total software engineering experience gained through work, education, coursework, training, research or similar in any area.

  • 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

  • Multimodal Classification (Natural Language Processing, Computer Vision)
  • Experience building reusable embeddings, applications and fine tuning of large language models.
  • Deep understanding of all aspects of machine learning model lifecycles (from prototypes, feature engineering, training, inference, deployment, monitoring).
  • Strong statistical and experimental foundation and acumen to develop insights from data.

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