Uber | Senior Staff Machine Learning Engineer – Search and Discovery | New York, NY | United States | BigDataKB.com | 2023-01-16

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Job Location: New York, NY

Job Detail:

About the role:

Leads efforts within the organization to drive the design, development, optimization, and productionization of ML or ML-based solutions and systems that are used to solve strategically important problems. Has extensive experience and expertise in large scale Applied ML (Recommender systems, Search, Ads, Content relevance etc.) and Deep Learning who can work across charters and many partner teams. Sr Staff Engineers at Uber are expected to have a deep impact on a wide variety of technology decisions, spanning many projects across an entire org, and in many cases multiple orgs.


About the Team:

Founded in August 2014, Uber Eats has become the largest food delivery app globally, and is the fastest growing food delivery platform in the world. We have doubled our gross bookings in just over the last year!
The Discovery Intelligence team is responsible for building the underlying ML/AI models to power a personalized and delightful customer experience across all product surfaces including search, feed, storefront, checkout, etc for Uber’s multi-vertical Delivery business (Eats, Grocery, Convenience Stores, Alcohols, and Prescription etc). As the world moves towards increased adoption of delivery services, we believe that effortless discovery will be one of the biggest product differentiators in the years to come.
The Discovery Intelligence team has 3 charters:
  • Feed Relevance – feed ranking, user lifecycle modeling, eater and store embeddings etc
  • Search and Retrieval – search ranking, semantic retrieval layer, query and document understanding, search suggestions.
  • Shopping Intelligence – Attribute extraction & product matching, item replacement recommendation, item ranking, storefront personalization etc.
Checkout some of our work here – https://www.uber.com/blog/uber-eats-recommending-marketplace/
Come join us in order to be part of a thriving culture, while solving exciting problems at scale.


Minimum qualifications:

  • PhD or equivalent in Computer Science, Engineering, Mathematics or related field AND 4-years full-time Software Engineering work experience OR 7-years full-time Software Engineering work experience, WHICH INCLUDES 4-years total technical software engineering experience in one or more of the following areas:
  • Programming language (e.g. C, C++, Java, Python, or Go)
  • Large-scale training using data structures and algorithms
  • Modern machine learning algorithms (e.g., tree-based techniques, supervised, deep, or probabilistic learning)
  • Machine Learning Software such as Tensorflow/Pytorch, Caffe, Scikit-Learn, or Spark MLLib

  • Note the 4-years total of specialized software engineering experience may have been gained through education and full-time work experience, additional training, coursework, research, or similar (OR some combination of these). The years of specialized experience are not necessarily in addition to the years of Education & full-time work experience indicated.

Technical skills:

Required:
  • Deep Learning
  • Scalable ML architecture
  • Feature engineering and management
Preferred:
  • NLP modeling
  • Privacy-aware/bias-free/Interpretable ML
  • Personalization
  • Optimization (RL/Bayes/Bandits)

For New York, NY-based roles: The base salary range for this role is $243,000 per year – $270,000 per year.For San Francisco, CA-based roles: The base salary range for this role is $243,000 per year – $270,000 per year.For Seattle, WA-based roles: The base salary range for this role is $243,000 per year – $270,000 per year.For Sunnyvale, CA-based roles: The base salary range for this role is $243,000 per year – $270,000 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.




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