About the job
The Consumer Incentives team is responsible for the profitability and growth trajectory of Uber's business across various verticals, including food and grocery. Our objective is to enhance the customer experience by making it more pleasant and affordable. The team addresses complex challenges in machine learning, optimization, and distributed systems to power products that serve hundreds of millions of individuals globally.
Responsibilities
1. Identifying strategic technical investments to push the efficiency frontier and boost business growth.
2. Leading teams to design and implement ML/optimization solutions to meet ambitious business goals.
3. Managing end-to-end project execution, from scoping and offline evaluation to experimentation, production, and post-launch operation.
4. Collaborating with cross-functional teams, including product, operations, and science partners.
Qualifications
Minimum
1. Master (or equivalent in Computer Science, Engineering, Mathematics or related field) with 6+ years of full-time ML engineering experience
2. Expertise in deep learning and optimization algorithms.
3. Experience with ML frameworks such as PyTorch and TensorFlow.
4. Experience building and productionizing innovative end-to-end Machine Learning systems.
5. Proficiency in one or more coding languages such as Python, Java, Go, or C++.
6. Strong communication skills and can work effectively with cross-functional partners.
Preferred
1. PhD in relevant fields (CS, EE, Math, Stats, etc.) with a focus on Machine Learning and 4+ years of experience in ML role with an emphasis on data and experiment driven model development.
2. Experience in serving and monitoring online training systems such as real time recommendation systems.
3. Experience designing and implementing novel metrics for performance evaluation.
4. Proven track record in conducting experiments and tracking models in high-complexity environments.