ML Infrastructure Engineer

A Day in the Life

As a member of our software engineering infra team, you'll solve technical challenges, including upgrading and implementing state-of-the-art software infrastructure. The team builds a high-performance, high availability, globally distributed ecosystem platform of services that in turn provide the foundation for rapid development of novel new systems that integrate into that ecosystem and improve it.

Our infra team is responsible for providing and maintaining scalable infrastructure with high throughput and low latency to our bidding ecosystem. You will be exposed to the whole pipeline of model delivery, including training, serving, and optimizations, etc.

The Impact You'll Make

• Design, develop, and maintain large-scale distributed systems

• Collaborate with various engineering teams to meet a wide range of technological challenges

• Work closely with our research science team and backend team to contribute and influence the roadmap of our products and technologies

• Influence and inspire team members

• Speed up the performance of our online models

• Optimize the model delivery pipeline

Who You Are

• Have 0-2 years of experience and a minimum of a BS and/or MS in Computer Science

• Have excellent knowledge of computer science fundamentals including data structures, algorithms, and coding

• Good experience with C++, Python and/or Golang is a plus

• Experience independently creating and maintaining projects

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AppLovin is proud to be an equal opportunity employer that is committed to inclusion and diversity. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status, or other legally protected characteristics. Learn more about EEO rights as an applicant here.

 

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To support an efficient and fair hiring process, we may use technology-assisted tools, including artificial intelligence (AI), to help identify and evaluate candidates. All hiring decisions are ultimately made by human reviewers.

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