Edge AI Engineer

Accountabilities

• Design, optimize, and deploy machine learning models that operate efficiently on edge devices.
• Balance AI development expertise with systems-level engineering skills to create reliable solutions under real-world hardware and connectivity constraints.
• 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

• 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.
• 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.