AI Systems Engineer
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AI Systems Engineer
100,000–150,000 / Year
Location
Remote
Experience
Mid
Posted
Jul 30, 2026
Apply by
August 29, 2026
Applicants
0
Early applicantEasy applyFull-timeWork from Home
Job Description
AI Systems Engineer- Remote
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: AI Systems Engineer
Location: 100% Remote (United States)
Position Type: Full-time, Direct W2
Salary Range: $100,000–$150,000 Annually
Experience: 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 AI Systems 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 [\[email protected\]](/cdn-cgi/l/email-protection) or contact us at (908) 650-6699. Learn more about Bright Vision Technologies at [www.bvteck.com](http://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.
Key Responsibilities
- Design, optimize, and deploy machine learning models for edge devices.
- Implement model compression, quantization, and pruning techniques.
- Ship reliable AI capabilities on mobile and embedded platforms.
- Perform performance engineering and profiling of AI systems.
- Address on-device privacy and security considerations.
Requirements
- Bachelor's or Master's degree in Computer Science
- Computer Engineering
- or a related field
Skills Required
PythonC++Model compressionQuantizationPruningEdge inference frameworksMobile hardware architecturesEmbedded hardware architecturesPerformance engineeringProfilingCommunicationCross-functional collaborationCustom NPU toolchainsDSP toolchainsFederated learningOn-device personalizationLLM optimization for on-device inference
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