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Edge ML Engineer

$100K–$150K

Bright Vision Technologies · Charlotte, NC · Remote · Full-time

Build · Found · posted 3 days ago

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Experience asked for: at least 6 years

Read out of the requirements below, in the employer's own words — not from a dropdown. Where a posting lists several requirements we take the largest, because a requirements list is a list of things you need all of.

Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential. Job Title: Edge ML Engineer Location: 100% Remote (U.S.) Position Type: Full-time, Direct W2 Salary Range: $100,000–$150,000 Annually Experience Required: 6+ years Job Summary We are looking for an Edge ML Engineer to design, optimize, and deploy machine learning models that run efficiently on resource-constrained edge devices, including mobile platforms, embedded systems, and specialized accelerators. The role requires deep expertise in model compression, quantization, and hardware-aware optimization, along with strong systems engineering skills to ship reliable AI capabilities outside the data center. The ideal candidate has shipped edge AI in production environments where compute, memory, energy, and connectivity constraints fundamentally shape the engineering trade-offs. Required 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 Preferred Qualifications • 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 How to Apply Would you like to know more about this opportunity? Learn more about Bright Vision Technologies at www.bvteck.com.

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