Machine Learning Engineer II

New York, NY, US • Posted 2 days ago • Updated 3 hours ago
Full Time
On-site
USD $171,000.00 - 190,000.00 per year
Fitment

Dice Job Match Score™

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Job Details

Skills

  • Art
  • Use Cases
  • Mathematics
  • Statistics
  • Research
  • FOCUS
  • Deep Learning
  • Optimization
  • Algorithms
  • PyTorch
  • TensorFlow
  • Python
  • Java
  • C++
  • Publications
  • Machine Learning (ML)
  • Apache Spark
  • Apache Hive
  • Apache Kafka
  • Apache Cassandra
  • Communication
  • Law
  • Legal
  • Collaboration

Summary

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 You'll do

- Innovate and productionize start-of-the-art recommendation models, and customize for Uber's use cases.
- Design and build the end-to-end large-scale ML systems to power the HomeFeed Recommendation.
- Improve the Feed Model ML Quality, Model Serving foundation and the Data foundation.
- Collaborate with cross-functional and cross-team stakeholders.

Basic Qualifications

- PhD in relevant fields (CS, EE, Math, Stats, etc.) with recommendation system research experiences or 3 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 in simplifying/converting business problems into ML problems.
- Experience developing complex software systems scaling to millions of users with production quality deployment, monitoring and reliability.
- Experience with any of the following: Spark, Hive, Kafka, Cassandra.
- Strong communication skills and can work effectively with cross-functional partners.

For New York, NY-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year.

For San Francisco, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 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. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link [](;br>
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](;br>
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.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 90958168
  • Position Id: c35d00f121becf21e5a2d73e54cb22d8
  • Posted 2 days ago
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