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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…
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$135k–$155k/yr
Full-time
bachelor degree, postgraduate degree
Visa sponsorship available
Posted 1d ago
Apply by Nov 4
~40 hrs/week
Remote in United States
Responsibilities
Design, optimize, and deploy machine learning models for resource-constrained edge devices such as mobile and embedded systems. Ensure reliable AI performance by managing compute, memory, and energy constraints in production environments.
Requirements
Requires a Bachelor's or Master's degree in Computer Science or a related field and at least six years of experience in ML engineering. Candidates must possess strong proficiency in Python and C++, along with hands-on experience in model compression and hardware-aware optimization.
Full job description
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
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
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.
BRIGHT VISION TECHNOLOGIES is one of the fast growing company of the region provides Corporate Training, Training Infrastructure and IT Consultations Services. Our clientele are practically Who's Who of the corporate World, from multinationals to IT Companies to large PSUs; the list is an enviable one.
BRIGHT VISION TECHNOLOGIES has expertise in imparting services on higher-end platforms viz. J2EE, Server Side Technology & Enterprise Architecture, Rational Suite, Project Management, Oracle, Lotus Notes, IBM Products, UNIX (LINUX, SOLARIS, AIX, HP) Administration, Windows, Data warehousing, Portal Servers, Web Server and Application Server. It is our constant endeavor to serve our customers wherever they maybe geographically located in the highest traditions of professionalism.
Offices: No.163/c,V.R.G Complex, N.S.R Road , Saibaba Colony, Coimbatore, TamilNadu 641011, IN · No.462 Main Road, A.Sembulichampalayam, Erode, TamilNadu 638501, IN
Corporate TrainingIT ConsultantingSoftware Developmentand Business Process Outsourcing
How many Engineering jobs are open in Carrollton, TX right now?
There are currently 218 open engineering positions in Carrollton, TX listed on Clera. New openings are added daily as companies post roles.
Which companies are hiring for Engineering roles in Carrollton, TX?
Companies currently hiring include Bright Vision Technologies, ECS Group of Companies, LiquidStack, Convergint, Thermo King, among others. Browse the listings above to see every active employer.
Are there remote or hybrid Engineering jobs in Carrollton, TX?
Yes — 60 of the 218 open engineering positions offer remote or hybrid work (53 remote, 7 hybrid).
How do I apply for Engineering jobs in Carrollton, TX?
Each listing links directly to the employer's application page. Apply early — fresh listings get the most recruiter attention in the first two weeks.