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Edge AI Engineer

jobgether · US

RemoteExternal listingfull-time19 days ago

About The Role

  • **This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Edge AI Engineer based in United States.**
  • The role offers an opportunity to design and deliver advanced artificial intelligence solutions that operate beyond traditional cloud environments.
  • You will focus on building efficient machine learning systems optimized for mobile, embedded, and resource-constrained edge platforms.
  • The position combines machine learning expertise, systems engineering, and performance optimization to bring AI capabilities into real-world applications.
  • You will work on challenging problems involving model efficiency, hardware constraints, privacy, and reliability.
  • This role is ideal for an engineer passionate about deploying production-grade AI where speed, power, and scalability matter.
  • You will collaborate with cross-functional teams to transform innovative AI concepts into practical, high-impact solutions

### Accountabilities

The Edge AI Engineer will be responsible for designing, optimizing, and deploying machine learning models that operate efficiently on edge devices. This role requires a balance of AI development expertise and systems-level engineering skills to create reliable solutions under real-world hardware and connectivity constraints.

  • Design, optimize, and deploy machine learning models for mobile platforms, embedded systems, and specialized edge accelerators.
  • Apply model compression, quantization, pruning, and other optimization techniques to improve AI performance and efficiency.
  • Develop production-ready edge AI solutions using Python, C++, and relevant machine learning frameworks.
  • Analyze and optimize model performance through profiling, benchmarking, and hardware-aware engineering practices.
  • Deploy and maintain machine learning models across mobile and embedded environments.
  • Work with hardware architectures and edge computing constraints to make effective engineering trade-offs.
  • Implement solutions that address on-device privacy, security, and reliability requirements.
  • Collaborate with product, software, hardware, and research teams to deliver scalable AI capabilities.
  • Contribute to improvements in edge AI development practices, tools, and deployment workflows.

## Requirements

The ideal candidate brings strong machine learning engineering experience with a proven ability to build and deploy AI solutions outside traditional data center environments. They should combine technical depth, problem-solving skills, and the ability to collaborate effectively across engineering teams.

  • Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related technical field.
  • 6+ years of experience in machine learning engineering, including significant experience with edge or mobile AI applications.
  • Strong programming skills in Python and C++.
  • Hands-on experience with model compression, quantization, pruning, and optimization techniques.
  • Experience working with at least one major edge inference framework.
  • Strong understanding of mobile and embedded hardware architectures.
  • Proven experience deploying machine learning models into production environments.
  • Strong performance engineering, profiling, and troubleshooting skills.
  • Knowledge of on-device privacy and security considerations.
  • Excellent communication skills with the ability to collaborate across technical and business teams.
  • Experience with custom NPU or DSP toolchains is preferred.
  • Familiarity with federated learning, on-device personalization, or safety-critical edge deployments is a plus.
  • Experience optimizing large language models for on-device inference is highly desirable.

## Benefits

  • Competitive annual salary range of **$100,000–$150,000**.
  • Fully remote position within the United States.
  • Full-time direct employment opportunity.
  • Opportunity to work on cutting-edge AI and machine learning technologies.
  • Career growth opportunities within an established technology organization.
  • Collaborative environment focused on innovation and advanced engineering solutions.

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