What are the responsibilities and job description for the Junior Hardware Optimization Engineer position at Jobright.ai?
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Job Summary:
Netradyne engages in improving fleet safety through computer vision and in-depth data analysis. They are looking for an experienced Model Optimization Engineer to join their technology team, focusing on benchmarking and optimizing internal models for performance improvements.
Responsibilities:
• Work with State-of-the-Art models such as VLMs, Vision Encoders, and other model architectures to get performance improvements (most likely in the form of throughput or memory)
• Work on Edge related model optimizations considering hardware constraints
• Apply post-training model compression techniques from the latest research papers
• Perform performance optimization of ML training code to extract best performance from available hardware
Qualifications:
Required:
• Familiarity with the internals of various SOTA vision model architectures
• Familiarity with SOTA VLMs and an understanding of concepts involved in running inference.
• Some Familiarity with one of the Cloud Providers (AWS, Azure, etc.)
• Excellent programming skills in Python
• Be self-driven and demonstrate the ability to derive results with limited supervision.
• Bachelor's Degree in Computer Science or similar field required
Preferred:
• Experience in performance optimization of ML code (both training and inference).
• 2 years of experience writing performant training and inference code
Company:
Netradyne engages in improving fleet safety through computer vision and in-depth data analysis. Founded in 2015, the company is headquartered in San Diego, California, USA, with a team of 501-1000 employees. The company is currently Late Stage. Netradyne has a track record of offering H1B sponsorships.
