채용
Required Skills
Python
Java
Go
PyTorch
TensorFlow
Kafka
Spark
Machine Learning
About the Role
The Uber Eats 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 Uber Eats'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.
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What You'll do
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Innovate and productionize start-of-the-art recommendation models, and customize for Uber's use cases.
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Design and build the end-to-end large-scale ML systems to power the Home Feed Recommendation.
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Improve the Feed Model ML Quality, Model Serving foundation and the Data foundation.
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Collaborate with cross-functional and cross-team stakeholders.
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Basic Qualifications
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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.
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Expertise in deep learning, recommendation systems, or optimization algorithms.
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Experience with ML frameworks such as Py Torch and Tensor Flow.
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Experience building and productionizing innovative end-to-end Machine Learning systems.
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Proficiency in one or more coding languages such as Python, Java, Go, or C++.
Preferred Qualifications:
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Publications at industry recognized ML conferences.
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Experience in simplifying/converting business problems into ML problems.
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Experience developing complex software systems scaling to millions of users with production quality deployment, monitoring and reliability.
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Experience with any of the following: Spark, Hive, Kafka, Cassandra.
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Strong communication skills and can work effectively with cross-functional partners.
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For New York, NY-based roles: The base salary range for this role is USD**$171,000 per year**
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USD**$190,000 per year**.
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For San Francisco, CA-based roles: The base salary range for this role is USD**$171,000 per year**
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USD**$190,000 per year**.
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For Sunnyvale, CA-based roles: The base salary range for this role is USD**$171,000 per year**
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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 https://jobs.uber.com/en/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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Pros
Flexible hours and schedule
Meeting different people and cultures
Make your own hours
Cons
Inconsistent and low pay
Safety concerns with passengers
Traffic and difficult drivers
Salary Ranges
23,534 data points
Junior/L3
Mid/L4
Senior/L5
Staff/L6
Junior/L3 · Data Scientist L3
0 reports
$145,456
total / year
Base
-
Stock
-
Bonus
-
$123,638
$167,274
Interview Experience
5 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Offer Rate
40%
Experience
Positive 80%
Neutral 20%
Negative 0%
Interview Process
1
Application Review
2
Online Assessment
3
Recruiter Screen
4
Technical Phone Screen
5
Case Study/Analytics Test
6
Final Loop/Panel Interview
7
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Case Study
Technical Knowledge
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