Software Engineer II - Machine Learning

$158,000 - $175,500/Yr

Uber - Seattle, WA

Full-time - Mid Level

Seattle, WA

Transit and Ground Passenger Transportation

About the position

The UberEats Feed is a critical component of our service, acting as the primary interface for users and merchants alike. For users, the Feed is designed to help them discover the best restaurants and grocery stores that meet their needs, while also providing a gateway to explore the extensive selection available through UberEats. For merchants, the Feed serves as the main platform to showcase their products and attract potential customers. As a Machine Learning Engineer in this role, you will tackle a variety of open-ended, challenging, and impactful problems that directly influence the user experience and merchant visibility. In this position, you will innovate and productionize state-of-the-art recommendation models tailored specifically for Uber's unique use cases. You will be responsible for designing and building large-scale machine learning systems that power the HomeFeed Recommendation, ensuring that our users receive the most relevant and personalized suggestions. Additionally, you will work on improving the quality of the Feed Model ML, enhancing the model serving foundation, and strengthening the underlying data infrastructure. Collaboration will be key, as you will engage with cross-functional teams and stakeholders to align on objectives and deliver impactful solutions.

Responsibilities

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

Requirements

• PhD in relevant fields (CS, EE, Math, Stats, etc.) with recommendation system research experience or a minimum of 2 years of industry experience focused 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++.
• Experience with technologies such as Spark, Hive, Kafka, or Cassandra.
• Strong communication skills and the ability to work effectively with cross-functional partners.

Nice-to-haves

• Publications at industry-recognized ML conferences.
• Experience in simplifying or converting business problems into machine learning problems.
• Experience developing complex software systems that scale to millions of users with production quality deployment, monitoring, and reliability.

Benefits

• Participation in Uber's bonus program.
• Potential equity award and other types of compensation.
• Various health and wellness benefits as detailed on the Uber careers benefits page.