Live opening · Posted 16 hours ago
At a glance
The key details from the original listing.
About the role
Description supplied by the original job listing.
About the role and team
The Rider Intelligence team powers personalization across Uber’s app homepage, helping users discover and access the most relevant services at the right time. Our work spans ranking homepage components, predicting and suggesting users’ next destinations, understanding user intent to deliver tailored experiences, presenting promotions at the right time, and optimizing the overall homepage experience across multiple business lines, including Rides, Eats, Grocery, and more.
As a Staff Machine Learning Engineer, you will shape the technical and scientific direction across these problem domains and lead the design and development of ML solutions, such as real-time sequential recommendation models, intent-aware ranking, and LLM-based and agentic solutions that go beyond traditional retrieval and ranking approaches. You will partner closely with product teams to deliver personalized user experiences, drive technical strategy across teams, and mentor engineers at various levels to elevate the team's technical excellence.
What You’ll Do
Drive ML technical strategy: Shape the technical and scientific direction of homepage personalization and recommendation systems.
Build advanced ML solutions: Lead the development of sequential recommendation models, intent-aware ranking, and LLM-based and agentic solutions.
Deliver product impact: Partner with cross-functional teams to improve user experience, engagement, and business outcomes across Uber’s business lines.
Provide technical leadership: Drive engineering excellence, influence technical decisions across teams, and mentor ML engineers.
Basic Qualifications
Deep expertise in machine learning, deep learning, and recommendation systems, including ranking, sequential modeling, and transformer architectures.
Strong programming skills in Python3 with hands-on experience using ML frameworks such as PyTorch or TensorFlow.
Proven track record of leading complex ML initiatives, driving measurable business impact, and influencing technical direction across teams.
Preferred Qualifications
8+ years of industry experience designing, developing, and deploying machine learning models in large-scale production environments.
Master's or PhD degree in Computer Science, Machine Learning, or a related field.
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