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Sr Staff Engineer, Machine Learning

Sr Staff Engineer, Machine Learning

UberSan Francisco, CA, United States
30+ days ago
Job type
  • Full-time
Job description

About the Role

We are looking for a Sr Staff Machine Learning Engineer to join the Eats Search Ranking Team. You will play a critical tech lead role in improving relevance and ranking for search results across all Uber Eats surfaces. Your work will have significant impact on the search experience for millions of Uber Eats users worldwide.. You will leverage your expertise in data analysis, machine learning, and Engineering to drive insights and optimize search algorithms, ultimately improving user satisfaction and operational efficiency.

What the Candidate Will Do :

  • Lead the team in design, development, and deployment ofstate-of-the-art machine learning models and algorithms to solve business problems and improve product performance.
  • Collaborate with applied / data scientists, software engineers, and product managers to understand requirements, define project goals, and deliver high-quality solutions.
  • Set long term technical direction for the team and uphold high engineering and ML quality bar
  • Provide technical leadership and direction to fellow software & ML engineers in the team
  • Identify new business opportunities to solve problems with the right technologies, and stay up-to-date with the latest advancements in machine learning techniques and technologies.

Basic Qualifications :

  • Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related technical field
  • 9+ years of experience in developing and deploying machine learning models and algorithms in production environments
  • Deep understanding of machine learning algorithms and ranking / recommendation systems, and strong system design skills
  • Excellent communication skills and the ability to collaborate effectively with cross-functional teams
  • Strong programming skills in languages such as Python, Java, or C++
  • Preferred Qualifications :

  • Ph.D. degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related technical field
  • Experience directly tech leading a 10+ machine learning team focusing on large scale search and ranking applications.
  • Familiarity with latest development in the field of deep learning, LLM, generative AI, recommendation system and related fields. Track record of applied research is a plus.
  • For San Francisco, CA-based roles : The base salary range for this role is USD$257,000 per year - USD$285,500 per year.

    For Seattle, WA-based roles : The base salary range for this role is USD$257,000 per year - USD$285,500 per year.

    For Sunnyvale, CA-based roles : The base salary range for this role is USD$257,000 per year - USD$285,500 per year.

    For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link https : / / www.uber.com / careers / benefits.

    Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.

    Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.

    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.

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    Staff Machine Learning Engineer • San Francisco, CA, United States

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