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Edge ML Engineer

Bright Vision Technologies
Posted 2 days ago, valid for 20 days
Location

Apex, NC, US

Salary

$100,000 - $150,000 per year

Contract type

Full Time

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Sonic Summary

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  • Bright Vision Technologies is seeking an Edge ML Engineer for a fully remote, full-time position with a salary range of $100,000 to $150,000 annually.
  • The role requires a minimum of 6 years of experience in machine learning engineering, particularly with edge or mobile AI applications.
  • Candidates should have a strong proficiency in Python and C++, along with hands-on experience in model compression and deployment on resource-constrained devices.
  • The ideal applicant will possess deep expertise in hardware-aware optimization and a solid understanding of mobile and embedded hardware architectures.
  • Interested individuals can apply by sending their resume to jaya@bvteck.com or contacting the company directly.
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? For immediate consideration, please send your resume to jaya@bvteck.com or contact us at (908) 505-3545. Learn more about Bright Vision Technologies at www.bvteck.com.

Bright Vision Technologies is an Equal Opportunity Employer.

Equal Employment Opportunity (EEO) Statement

Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall.

BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment.




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