At Uber, they ignite opportunity by setting the world in motion. They take on big problems to help drivers, riders, delivery partners, and eaters get moving in more than 600 cities around the world.
They welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have a curiosity, passion, and collaborative spirit, work with them, and let’s move the world forward, together.
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. They also consider qualified applicants regardless of criminal histories, consistent with legal requirements.
Uber AI’s mission is to optimize and innovate Uber’s products and businesses using machine learning and AI. The group consists of Uber’s machine learning platform team which enables machine learning at scale, AI building blocks which enable product teams to build unique experiences and engagements with product teams on their business problems.
The group consists of machine learning engineers, mobile engineers, backend engineers, and research scientists and engineers.
About The Role
Uber AI Engagements collaborates with partner teams across Uber to deliver innovative Machine Learning/AI solutions for core business problems. You will work closely with engineering, product, and data science teams to understand business problems and the potential for ML/AI solutions. You will deliver these solutions from inception to production. Machine Learning Engineers have deep domain knowledge in ML/AI and the ability to apply that knowledge to diverse problem domains involving multiple stakeholders.
What You’ll Do
- Develop innovative ML/AI solutions for challenging business problems that are fundamental for Uber.
- Partner with product teams to analyze key business problems.
- Collaborate with data science and engineering teams to integrate and validate machine learning solutions end-to-end.
- Deliver enduring value in terms of software and modeling artifacts.
- Masters in Computer Science with a specialization in ML, related field, or equivalent industry experience.
- 2+ years of industry experience in applied ML, or a Ph.D. with some industry experience obtained through e.g. internships.
- Proficiency in Python.
- Experience with ML frameworks such as PyTorch and TensorFlow.
- 4+ years of industry experience in applied ML, or a Ph.D. and 2+ years of industry experience.
- Expertise in Bayesian optimization, probabilistic machine learning, knowledge graphs, recommendation systems, or deep learning.
- Proficiency in one or more coding languages such as Java, Go, C, C++.
- Experience with any of the following: Spark, Hive, Kafka, Cassandra.
- Ability to innovate, as demonstrated by a track record of software artifacts or publications.
- Ability to deliver end-to-end solutions, including data preparation, training, and deployment.
- Experience working with product teams.
- Ability to work with ambiguous problem definitions.
- Proven ability to communicate technical knowledge to a business audience.
- Collaborative attitude and constructive approach.
- Salary Offer 0 ~ $3000
- Experience Level Junior
- Total Years Experience 0-5
- Dropdown field Option 1