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Principal ML Engineer
3 months ago
Job Overview:
Arm is seeking a Principal ML Engineer to join our Verification Efficiency team in Austin, Texas. This team member will be responsible for writing, deploying, improving, and maintaining software that increases Arm's verification efficiency. This software includes applications based on ML (machine learning) techniques, and may also use other techniques like traditional statistics or optimization theory where appropriate and effective.
The Verification Efficiency team's primary responsibility is to reduce the cost of testing and verifying the functionality of new Arm products and to improve the quality of verification results. Our team is part of the broader Productivity Engineering group, which works in a variety of ways to help all of Arm's engineering divisions do their work more effectively.
Responsibilities:
- Writing, debugging, refactoring, testing and profiling code that is delivered in user applications, libraries, and services
- Improving and maintaining our software development infrastructure and methodology
- Understanding customer needs and use-cases, and collaborating with them to design solutions that are both compelling and cost-effective for Arm
Required Skills and Experience:
- Excellent Python programming abilities
- Deep knowledge of software engineering methodologies and tools
- Solid understanding of computer science fundamentals
- Experience using ML libraries and deployment platforms
- Demonstrated technical leadership at the individual contributor level
"Nice To Have" Skills and Experience:
- Experience performing hardware or software verification or testing
- Experience writing distributed computing applications
- Knowledge of ML models, statistics, optimization, and similar techniques
- Experience with scikit-learn, Kubernetes, Docker and AWS
In Return:
Arm is an equal opportunity employer, committed to providing an environment of mutual respect where equal opportunities are available to all applicants and colleagues. We are a diverse organization of dedicated and innovative individuals, and don't discriminate on the basis of any characteristic.
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