Sr Software Engineer (Machine Learning)

Key Skills

3D data processing, Aartificial intelligence, C Programming, C++, Data science techniques, Java Programming, Large data sets, Machine learning techniques, MLOps tools, Natural Language Processing (NLP), Optimization, Python Programming

Job Description

Canvas is one of the core pillars under Michelangelo, Uber's machine learning platform. This team focuses on building and standardizing model dev experiences for ML Engineers and Data Scientists. We build and operate the dev tool known as Canvas, where ML engineers can develop the model solutions for their business needs in all critical ML phases, such as feature engineering, training, serving, ML-Ops, and monitoring. With the Canvas tool, users can iterate quickly and collaboratively during model dev time to build their ML solution, and the solution will be automatically scaled up to run robustly when it is deployed into production.

Now we are extending our modeling support to generative AI and large scale models. We are looking for talents with experience building and productionize large scaling models solving business problems.

This team is formed by a group of talents with various expertise, such as modeling techniques, batch data processing optimization, orchestrations, dev tool development, and distributed algorithms.

We also have a great reputation in the industry building leading edge solutions for ML platforms.

What You'll Do

• Provide solutions for data curation pipelines.
• Develop the platform for training / analyzing / serving large scale models, embedding, NLP models.
• As a core member of Michelangelo, work with team members in US to develop solutions for NLP and generative AI used by all ML engineers in Uber.

Basic Qualifications

• PhD or equivalent in Computer Science, Engineering, Mathematics or related field
• Programming language (e.g. C, C++, Java, Python, or Go)
• NLP or embeddings
• Experience on curating and bootstrapping dataset for large scale NLP problems
• Building, Analyzing, and Serving embeddings
• Experience on solve NLP problems
• Model zoo, base model management for large size models

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.