Staff Machine Learning Engineer - Applied AI

$218,000 - $242,000/Yr

Uber - San Francisco, CA

Full-time - Mid Level

Remote - San Francisco, CA

Transit and Ground Passenger Transportation

About the position

Uber's Applied AI team is at the forefront of leveraging cutting-edge artificial intelligence and machine learning technologies to enhance the Uber experience for millions of users globally. 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.

Responsibilities

• 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.
• Provide technical leadership and direction for the team.

Requirements

• PhD or equivalent in Computer Science, Engineering, Mathematics or related field.
• 2-years full-time Software Engineering work experience OR 5-years full-time Software Engineering work experience, which includes 3-years total technical software engineering experience in one or more of the following areas: Programming language (e.g. C, C++, Java, Python, or Go), Large-scale training using data structures and algorithms, Modern machine learning algorithms (e.g., tree-based techniques, supervised, deep, or probabilistic learning), Machine Learning Software such as Tensorflow/Pytorch, Caffe, Scikit-Learn, or Spark MLLib.
• 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.

Nice-to-haves

• Experience in a technical leadership role.
• Experience in modern deep learning architectures and probabilistic models.
• Experience in modern generative AI, such as transformer architectures, diffusion models and prompting.

Benefits

• Participation in Uber's bonus program.
• Eligibility for equity awards and other types of compensation.
• Various health and wellness benefits.