Staff Machine Learning Engineer, Mobility Matching
San Francisco, CA, USA
Posted on Wednesday, September 13, 2023
About The RoleWe are seeking a highly skilled and experienced Staff Machine Learning Engineer to join our Mobility Matching ML team at Uber. You will play a crucial role in developing and optimizing algorithms and systems that match supply (drivers) with demand (riders) in real-time. You will work on complex ML problems, leveraging data and algorithms to ensure efficient and reliable marketplace matching. Additionally, the team supports ML needs for matching vertical products (e.g., shared rides/pool, wait&save, etc.); via projects like predict demand, dynamic pricing, optimal wait times, learn rider preferences, etc. Your contributions will directly impact the experience of millions of users worldwide.The team is part of the Marketplace Dynamics org, a central pillar to Uber’s core technology. As the key brain of the company, we are the decision makers that make moving from point A to point B possible for every trip or order that Uber serves, from UberX to Eats to new verticals such as grocery, shared rides, and last mile delivery. We handle all the logic from making the dispatch (i.e., matching), predicting how long a delivery might take, to travel time estimates for potential dispatches and routing. What The Candidate Will Do
- Design, develop, and deploy state-of-the-art machine learning models and algorithms to solve business problems and improve product performance.
- Conduct exploratory data analysis and feature engineering to gain insights and improve model performance.
- Collaborate with applied/data scientists, software engineers, and product managers to understand requirements, define project goals, and deliver high-quality solutions.
- Conduct research and stay up-to-date with the latest advancements in machine learning techniques and technologies.
- Evaluate and integrate third-party machine learning libraries, tools, and frameworks to enhance our existing ML infrastructure.
- Optimize and fine-tune machine learning models for scalability, performance, and efficiency.
- Work on large-scale data processing and feature extraction pipelines to support machine learning workflows.
- Mentor and provide technical guidance to junior members of the team, fostering their professional growth and development.
- Collaborate with cross-functional teams to drive best practices in data management, data quality, and model deployment.
- Stay informed about industry trends, emerging technologies, and advancements in machine learning and artificial intelligence.
- A Bachelor's, or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related technical field
- 5-7+ years of experience in developing and deploying machine learning models and algorithms in production environments
- Strong programming skills in languages such as Python, Java, or C++
- Experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras
- Deep understanding of machine learning algorithms, statistical models, and their applications
- Excellent communication skills and the ability to collaborate effectively with cross-functional teams
- Ph.D. degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related technical field
- 8-10+ years of experience in developing and deploying machine learning models and algorithms in production environments
- Strong knowledge of deep learning/reinforcement learning/bandit exploration techniques and familiarity with modern research in the field is highly valued
- Proficiency in SQL and experience with relational and NoSQL databases
- A track record of research publications in top-tier conferences or journals, demonstrating expertise in machine learning or related areas, is a significant advantage
- Strong analytical and problem-solving skills are necessary to tackle complex machine learning challenges