Machine Learning Infrastructure Engineer
124 000 – 250 000 $в год
AppLovinPalo Alto и ещё 1 городБез опыта
PythonMachine LearningC++Distributed systemsGolanginfrastructureAlgorithmsData Structures
Описание
AppLovin is hiring an ML Infrastructure Engineer in Palo Alto, CA to build and maintain scalable distributed systems for its bidding ecosystem. The role focuses on model delivery pipeline performance, serving, and optimizations, and collaborates with research science and backend teams.
Responsibilities
- 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
Requirements
- 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
Nice to have
- Good experience with C++, Python and/or Golang is a plus
- Experience independently creating and maintaining projects
We offer
- Competitive total compensation package with a pay for performance rewards approach
- Total compensation at AppLovin is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience
- Equity, and other forms of incentive compensation (as applicable) may be provided as part of a total compensation package
- Medical, Dental, Vision, Life, Disability insurance
- 401(k) Retirement Plan
- Unlimited Discretionary Time Off
- 10 paid holidays per year
- 80 hours paid sick leave per year
- CA Base Pay Range $124,000–$250,000 USD
Hiring process
- The application window is expected to close within 30 days of the posting date
- 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.