
Reimagining transportation for a better world
Uber Technologies, Inc. (NYSE: UBER) is a leading ride-hailing platform headquartered in Mission Bay, San Francisco, CA. Founded in 2009, Uber has transformed transportation services, completing over 1.5 billion trips globally. The company went public in May 2019 and has raised $15.8 billion in fund...
Uber provides comprehensive healthcare, a robust employee stock purchase plan, generous paid vacation, and a four-week sabbatical after five years of ...
Uber fosters a culture of innovation and adaptability, continuously expanding its services beyond traditional ride-hailing. The company emphasizes wor...

Uber • San Francisco, USA
Uber is hiring a Senior Machine Learning Engineer to design and optimize ML-based solutions for their mobility and logistics platforms. You'll work with technologies like Python and AWS to impact millions of users. This role requires strong experience in machine learning and system optimization.
You have 5+ years of experience in software engineering with a focus on machine learning — you've designed, developed, and optimized ML systems that solve complex problems and have a deep understanding of ML infrastructure and deployment. Your expertise in Python and familiarity with cloud services like AWS enable you to build scalable solutions that meet production needs.
You are a collaborative team player who enjoys working with stakeholders to understand their requirements and translate them into technical solutions. Your experience with Kubernetes and container orchestration allows you to manage and scale ML models effectively, ensuring they perform well under varying loads.
You have a strong foundation in algorithms and data structures, which helps you to optimize ML models for performance and efficiency. You are comfortable with both supervised and unsupervised learning techniques and have experience in deploying models in production environments.
Your communication skills are top-notch — you can articulate complex technical concepts to non-technical stakeholders and work closely with cross-functional teams to drive innovation. You are proactive in identifying areas for improvement within existing systems and are always looking for ways to enhance ML capabilities.
Experience with big data technologies and frameworks such as Apache Spark or Hadoop would be a plus. Familiarity with data visualization tools and techniques can help you present insights derived from ML models effectively.
As a Senior Machine Learning Engineer at Uber, you will partner with various teams to design and develop ML solutions that enhance user experiences across our mobility and logistics platforms. You will lead efforts to improve our ML infrastructure, focusing on model development, training, and deployment processes. Your role will involve optimizing existing ML systems to ensure they scale effectively and meet the demands of millions of users.
You will be responsible for building and maintaining high-scale systems that power critical features such as routing algorithms and delivery predictions. Your work will directly impact the efficiency of our operations and the satisfaction of our users. You will also mentor junior engineers, sharing your knowledge and best practices in machine learning and software development.
Collaboration is key in this role — you will work closely with product managers, data scientists, and other engineers to define project scopes and deliverables. You will participate in code reviews and contribute to the overall technical direction of the team, ensuring that we adhere to best practices in software engineering and machine learning.
At Uber, we offer a dynamic work environment where innovation is encouraged. You will have the opportunity to work on projects that have a significant impact on our users and the transportation landscape. We provide competitive compensation and benefits, including flexible work arrangements to support a healthy work-life balance. Join us in redefining mobility and logistics through cutting-edge technology and machine learning.
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