Company Name:-
Uber

Job Location:-
Sunnyvale, CA

Job Summary:-
About the Team:
At Uber, we ignite opportunity by setting the world in motion.

We take on big problems to help drivers, riders, delivery partners, and eaters get moving in more than 600 cities around the world.

We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently.

If you have curiosity, passion, and collaborative spirit, work with us, and let’s move the world forward, together.

About the Role:
Software Engineer – Machine learning will be expected to be involved in machine learning solutions for all risk and fraud applications.

Our team applies a variety of machine learning algorithms to solve the problems in the risk domain.

You will benefit from Uber’s unique talent pool spanning from Uber machine learning platform to Uber AI, applying and extending their research and tools to our domain areas.

What the Candidate Will Do:
Depending upon your previous expertise and interest, you will be expected to be heavily involved in
Applying state-of-the art machine learning algorithms and researches to different business problems
Building and enhancing a scalable machine learning platform
Maintaining the existing ML models in production
Basic Qualifications:
At least 2 years of machine learning experience
Bachelor of Science (BS) in Computer Science, Physics, or Mathematics, or related field
ML background on classification, ranking or optimization
Master degree or above in computer science or related quantitative field
Strong coding skill in one main language
Experience in scripting language such as python, perl and shell scripts
Preferred Qualifications:
Previous expertise on distributed systems and/or ML Infra
Excited about scalability and reliability of systems
Previous domain expertise in some high-scale Applied ML field (Fraud/Risk, Cyber Security, Recommendation, search etcs )
At Uber, we ignite opportunity by setting the world in motion.

We take on big problems to help drivers, riders, delivery partners, and eaters get moving in more than 10,000 cities around the world.

We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently.

If you have the curio

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