Staff Machine Learning Engineer, Applied AI

Uber

Confirmed live today High trust
Hybrid

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Work type
Hybrid
Location
San Francisco, CASeattle, WASunnyvale, CA
Posted
110 days ago
Freshness
Confirmed live today

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Similar $229k
$174k $289k
below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $202,800–$254,750.

Based on 240 similar postings.

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About Uber

Uber Technologies, Inc. is the world’s largest, San Francisco-based mobile technology platform facilitating on-demand ride-hailing, food delivery (Uber Eats), and freight transportation across approximately 70 countries.

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TL;DR · Staff Machine Learning Engineer, Applied AI

The Staff Machine Learning Engineer - Applied AI joins the Applied AI team to deliver innovative solutions for core business problems. This role involves defining and leading the foundation model strategy for AI-native discovery experiences across Mobility and Delivery, specifically focusing on Search, Recommendations, and Conversational AI. You will own the end-to-end technical strategy, drive architecture decisions for multiple product surfaces, and lead cross-team initiatives spanning Retrieval, Ranking, Personalization, and LLM-powered assistants. Key responsibilities include defining long-term investment areas and mentoring senior engineers. The role requires deep expertise in transformers, retrieval systems, ranking, and embedding architectures. Candidates must demonstrate proficiency with PyTorch and distributed training while managing large-scale deep learning systems to solve complex problems in Personalization, Generative AI, Computer Vision, ML Optimization, and Geospatial AI.

What does a Machine Learning Engineer earn in California?

Median $236000 from 195 postings across 33 companies.

See salary data

What you'll do

  • Own the end-to-end technical strategy for foundation models across Search, Recommendations, and Conversational AI.
  • Drive architecture decisions that influence multiple product surfaces including Eats, Grocery, Retail, and Mobility.
  • Lead cross-team initiatives spanning Retrieval, Ranking, Personalization, and LLM-powered assistants.
  • Define long-term investment areas regarding building, fine-tuning, or partnering for models.
  • Mentor senior engineers and act as a technical multiplier across the organization.
  • Connect model improvements to specific business outcomes through strong product intuition.

What we're looking for

  • Master's degree or Ph.D. in Computer Science, Engineering, or Mathematics.
  • 8+ years of ML experience, including significant work on large-scale deep learning systems.
  • Demonstrated ownership of high-impact ML systems in search, recommendations, or conversational AI.
  • Deep expertise in transformers, retrieval systems, ranking, and embedding architectures.
  • Strong experience with PyTorch and distributed training.
  • Track record of influencing technical direction across teams.
  • Strong product intuition and ability to connect model improvements to business outcomes.
  • Experience leading multi-team ML initiatives (preferred).

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