Edge AI Engineer — On-Device ML & Edge Optimization

Polluxa, Inc.; United States; On-site; USD 150,000 - 190,000; Full time

Job summary

Bright Vision Technologies (BV Teck) seeks an experienced ML engineer focused on edge and mobile AI to advance on-device inference capabilities. You will design, optimize, and deploy models for constrained hardware, collaborating with cross-functional teams to meet performance and privacy requirements.

The ideal candidate has 6+ years in ML engineering, strong Python and C++, experience with model compression and edge frameworks, and a track record of production deployments on mobile or embedded

Qualifications

• Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related field.
• Six or more years of experience in ML engineering, with significant work on edge or mobile AI.
• Strong proficiency in Python and C++.
• Hands-on experience with model compression, quantization, and pruning techniques.
• Experience with at least one major edge inference framework.
• Solid understanding of mobile and embedded hardware architectures.
• Experience deploying ML models to production on mobile or embedded platforms.
• Strong performance engineering and profiling skills.
• Familiarity with on-device privacy and security considerations.
• Strong communication and cross-functional collaboration skills.
• Experience with custom NPU or DSP toolchains.
• Familiarity with federated learning or on-device personalization.
• Exposure to safety-critical or industrial edge deployments.
• Open-source contributions to edge AI frameworks.
• Experience optimizing LLMs for on-device inference.

Skills

Python

C++

Edge ML

Profiling

Communication

Education

Bachelor’s/Master’s in CS/CE or related field

Tools

NPUtoolchains

DSPtoolchains

Edge inference framework

Job description

Bright Vision Technologies (BV Teck) seeks an experienced ML engineer focused on edge and mobile AI to advance on-device inference capabilities. You will design, optimize, and deploy models for constrained hardware, collaborating with cross-functional teams to meet performance and privacy requirements.

The ideal candidate has 6+ years in ML engineering, strong Python and C++, experience with model compression and edge frameworks, and a track record of production deployments on mobile or embedded