Staff Machine Learning Engineer, Mobility Matching

Key Skills

Aartificial intelligence, Analytical and Problem solving, C++, Data Analysis, Deep Learning, Effective communication skills, Java Programming, Keras software library, Machine learning techniques, NoSQL, Python Programming, PyTorch, SQL, Statistics, TensorFlow

Job Description

We 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 Need / Bonus Points

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.

Basic Qualifications 

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

Preferred Qualifications

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

Uber is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.

Offices continue to be central to collaboration and Uber’s cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.

For San Francisco, CA-based roles: The base salary range for this role is $207,000 per year - $230,000 per year.

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.