Edge ML Engineer

About This Opportunity

Our talent team is representing a confidential technology organization seeking an Edge ML Engineer to design, optimize, and deploy machine learning models on resource-constrained edge devices. This is a 100% remote, full-time W2 position based in the United States.

This role requires deep expertise in model compression, quantization, and hardware-aware optimization, combined with strong systems engineering skills to deliver reliable AI capabilities on mobile platforms, embedded systems, and specialized accelerators. You'll work where compute, memory, energy, and connectivity constraints fundamentally shape engineering trade-offs.

Responsibilities

• Design and optimize machine learning models for efficient execution on edge devices
• Implement model compression, quantization, and pruning techniques to meet resource constraints
• Deploy production ML models to mobile and embedded platforms
• Conduct performance engineering and profiling to maximize on-device efficiency
• Collaborate cross-functionally to ship edge AI capabilities that balance technical constraints with product requirements
• Address on-device privacy and security considerations in deployed solutions
• Work with mobile and embedded hardware architectures to optimize inference performance

What We're Looking For

Required qualifications:

• Bachelor's or Master's degree in Computer Science, Computer Engineering, or related field
• 6+ years of experience in ML engineering, with significant edge or mobile AI work
• 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
• Proven track record deploying ML models to production on mobile or embedded platforms
• Strong performance engineering and profiling skills
• Familiarity with on-device privacy and security considerations
• Excellent communication and cross-functional collaboration abilities

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 We Work With You

Candidates apply directly through Get A Job.ai. Our recruiting team will conduct an initial screening to understand your background and ensure alignment with the role requirements. Once vetted, we'll submit your profile to our client for consideration. Please do not contact the client directly—all communication flows through our team to ensure a smooth, professional process.

Pay

Pay via Get A Job.ai: $100,000–$150,000 annually

Equal Employment Opportunity: Get A Job.ai is committed to equal employment opportunity for all applicants regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic under applicable law.