出海雷达

边缘 AI 工程师

Edge AI Engineer

AI开发工程限定地区(需当地身份)
公司Bright Vision Technologies
薪资$100,000 - $155,000/年
工作地点United States
地域资格限定地区(需当地身份)
时区要求日间重叠约 9 小时,基本正常作息
用工类型Full Time
发布时间今天
数据来源Himalayas
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注意地域限制:该职位明确限定在 United States 招聘。如果你是位于中国大陆的求职者,通常需要当地工作身份才能投递,或需与雇主确认是否接受独立合同(Contractor)形式合作。

Edge AI 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: Edge AI Engineer
Location: 100% Remote (U.S.)
Position Type: Full-time, Direct W2
Salary Range: $100,000–$155,000 Annually
Experience Required: 8+ 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 Edge AI 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.

Key Responsibilities
· Design and implement edge AI solutions optimized for diverse hardware including mobile SoCs, NPUs, and embedded accelerators.

  • Apply quantization, pruning, distillation, and architectural optimization to fit models within edge constraints.
  • Tune model performance for latency, energy efficiency, and memory footprint on target hardware.
  • Build cross-platform inference runtimes leveraging frameworks such as TensorFlow Lite, ONNX Runtime, and Core ML.
  • Optimize models for specific accelerator backends including DSPs, NPUs, and mobile GPUs.
  • Implement on-device model update, versioning, and rollback workflows that allow safe staged rollouts to large device populations and rapid recovery if a model release behaves unexpectedly in the field.
  • Design hybrid edge-cloud architectures that gracefully degrade based on connectivity and device capability.
  • Build telemetry pipelines that respect privacy while enabling continuous improvement.
  • Collaborate with hardware, firmware, and product teams to align AI capabilities with device constraints.
  • Implement secure execution paths, model protection, and integrity verification on edge devices.
  • Develop benchmarking suites that characterize accuracy, latency, and energy trade-offs across devices.
  • Drive responsible AI considerations including on-device privacy and bias evaluation.
  • Maintain comprehensive, current technical documentation — including architecture diagrams, design decisions, configuration references, runbooks, and operational procedures — so that the system remains supportable, auditable, and easy to onboard new engineers onto over time.
  • Stay current with edge AI hardware and software developments, regularly review release notes and community discussions, and translate noteworthy advances into concrete recommendations and adoption proposals for the team.

Required Qualifications
· Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field.

  • Eight 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 or contact us at (908) 505-3899. Learn more about Bright Vision Technologies at .
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.
Originally posted on Himalayas

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