Overview
Arm’s ML Research Group is actively seeking talented individuals for machine learning researcher positions in Austin, Texas. This opportunity is significant for those looking to advance their careers in a leading technology company, particularly in the field of machine learning optimization on constrained platforms.
Background & Relevance
The field of machine learning is rapidly evolving, with applications spanning various industries. Optimizing machine learning models for constrained environments is crucial, especially as devices become smaller and more resource-limited. This role focuses on several cutting-edge areas, including mixed-precision neural networks and on-device learning, which are vital for enhancing the efficiency and effectiveness of AI applications.
Key Details
- Position Type: Researcher
- Location: Austin, Texas, USA
- Focus Areas:
- Optimizing machine learning on constrained platforms
- Mixed-precision neural networks (binary/ternary models)
- Model design-space exploration for cost/accuracy optimization
- On-device learning and federated learning
- AutoML techniques
- Learning with limited data
- Matrix factorization for model size and runtime optimization
- Application Link: Job Posting
Eligibility & Participation
This position is open to PhD candidates and well-qualified Master’s students. Graduates nearing completion of their degrees are encouraged to apply, making this a great opportunity for those looking to transition into industry roles.
Submission or Application Guidelines
Interested candidates should send their resumes directly to Urmish Thakker at urmish.thakker@arm.com. This straightforward application process allows potential candidates to quickly express their interest in the position.
Additional Context / Real-World Relevance
The demand for machine learning professionals is increasing as organizations seek to leverage AI technologies for competitive advantage. Positions like these at Arm not only contribute to the advancement of machine learning techniques but also play a crucial role in the development of innovative solutions that can be applied across various sectors, including consumer electronics and automotive industries.
Conclusion
For those passionate about machine learning and looking to make an impact in a dynamic environment, this opportunity at Arm presents a promising career path. Interested individuals are encouraged to apply and explore the potential of contributing to groundbreaking research in machine learning optimization.
Category: Academic Jobs
Tags: machine learning, ml research, arm, austin, neural networks, federated learning, automl, data optimization
