Staff Machine Learning Engineer - UberEats Feed

Rocket Lab; San Francisco (CA); On-site; USD 223,000 - 248,000; Full time

Job summary

A leading tech company seeks a Machine Learning Engineer to innovate and enhance recommendation systems for their service. This role emphasizes the design of scalable ML solutions, leadership in a cross-functional environment, and the ability to translate complex problems into effective machine learning strategies. Candidates should possess substantial experience in machine learning, particularly with deep learning frameworks, and a strong academic background in a related field.

Benefits

Uber's bonus program

Equity award opportunities

Various employee benefits

Qualifications

• Minimum of 8 years industry experience in ML and recommendation systems.
• Experience building and productionizing end-to-end ML systems.
• Publications at recognized ML conferences are a plus.

Responsibilities

• Design and build large-scale ML systems for Home Feed recommendation.
• Lead research on new recommendation algorithms and systems.
• Collaborate with cross-functional teams to solve open-ended problems.

Skills

Deep Learning

Recommendation Systems

Optimization Algorithms

Machine Learning

Strong Communication Skills

Education

PhD or Master in CS, EE, Math, Stats

Tools

PyTorch

TensorFlow

Spark

Hive

Kafka

Cassandra

Job description

About the Role

The UberEats Feed is the front door to our service. It serves an important role for both users and merchants. For our users, the Feed helps them find a great restaurant or grocery store for their needs. It also serves as an important gateway for them to explore the breadth and depth of UberEats’s selection. For merchants, it is the main surface for which they get in front of potential customers to showcase their products. As a Machine Learning Engineer in this role, you will be able to work on various open-ended, challenging, impactful problems.

What the Candidate Will Do:

• Innovate and productionize start-of-the-art recommendation models, and customize them for Uber’s use cases.
• Design and build the end-to-end large-scale ML systems to power Home Feed recommendation systems.
• Lead research and design of new recommendation algorithms and systems.
• Collaborate with cross-functional and cross-team stakeholders to solve open-ended user and technical problems.
• Lead a team of strong machine learning engineers and xfn to deliver high-impact projects.
• Drive the long-term technical vision for the team in a specific recommendations domain.
• Drive cross-team initiatives with org level impact.

Basic Qualifications:

• PhD or Master in relevant fields (CS, EE, Math, Stats, etc.) with recommendation system research experiences and 8 years minimum of industry experience with a strong focus on machine learning and recommendation systems.
• Expertise in deep learning, recommendation systems, or optimization algorithms.
• Experience with ML frameworks such as PyTorch and TensorFlow.
• Experience building and productionizing innovative end-to-end Machine Learning systems.
• Proficiency in one or more coding languages such as Python, Java, Go, or C++.

Preferred Qualifications:

• Publications at industry recognized ML conferences.
• Experience with any of the following: Spark, Hive, Kafka, Cassandra.
• Strong communication skills and can work effectively with cross-functional partners.
• Experience in simplifying/converting business problems into ML problems.
• Experience designing and developing complex software systems scaling to millions of users with production quality deployment, monitoring and reliability.
• Experiences leading projects with org-level impact.

For San Francisco, CA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 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 is proud to be an Equal Opportunity/Affirmative Action 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.