The Role
Design, optimize, and deploy machine learning models for resource-constrained edge devices, including mobile and embedded platforms. Apply model compression, quantization, pruning, hardware-aware optimization, performance profiling, and systems engineering to deliver production-ready on-device AI. Collaborate cross-functionally while addressing compute, memory, energy, connectivity, privacy, and security constraints. Preferred work includes custom NPU/DSP toolchains, federated learning, safety-critical deployments, open-source contributions, and on-device LLM optimization.
Summary Generated by Built In
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: Intelligent Edge Engineer
Location: 100% Remote (U.S.)
Position Type: Full-time, Direct W2
Salary Range: $135,000–$155,000 Annually
Experience Required: 6+ years
Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position.
Job Summary:
We are looking for an Intelligent Edge 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
Preferred Qualifications
How to Apply
Would you like to know more about this opportunity? For immediate consideration, please send your resume to [email protected] or contact us at (908)676-4399. Learn more about Bright Vision Technologies at www.bvteck.com.
Bright Vision Technologies is an Equal Opportunity Employer
This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.
Job Title: Intelligent Edge Engineer
Location: 100% Remote (U.S.)
Position Type: Full-time, Direct W2
Salary Range: $135,000–$155,000 Annually
Experience Required: 6+ years
Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position.
Job Summary:
We are looking for an Intelligent Edge 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 [email protected] or contact us at (908)676-4399. Learn more about Bright Vision Technologies at www.bvteck.com.
Bright Vision Technologies is an Equal Opportunity Employer
Skills Required
- Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related field
- Six or more years of ML engineering experience with significant edge or mobile AI work
- 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
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The Company
What We Do
Bright Vision Technologies is a minority-owned organization founded in July 2020 and based in New Jersey, USA. The company specializes in delivering top-tier staffing and IT consulting services, including custom computer programming and systems design. Additionally, they are a product engineering firm with a flagship AI-powered talent intelligence and enterprise automation platform called Lumina, which helps transform IT into a strategic asset for their valued partners.
