Edge AI Engineer

Location: 100% remote within the United States

Salary: $100,000–$155,000 annually

Company

hirify.global is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.

What you will do

• Design and implement edge AI solutions for mobile SoCs, NPUs, embedded accelerators, DSPs, and mobile GPUs.
• Apply quantization, pruning, distillation, and architectural optimization to meet compute, memory, energy, and connectivity constraints.
• Build cross-platform inference runtimes using TensorFlow Lite, ONNX Runtime, Core ML, or comparable frameworks.
• Implement secure model update, versioning, rollback, telemetry, privacy, and integrity-verification workflows for large device populations.
• Design hybrid edge-cloud architectures and benchmarking suites covering accuracy, latency, energy efficiency, and memory usage.
• Collaborate with hardware, firmware, and product teams while maintaining technical documentation and evaluating new edge AI technologies.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field.
• At least 6 years of ML engineering experience with significant edge or mobile AI work; the position listing also specifies 8+ years of experience.
• Strong proficiency in Python and C++.
• Hands-on experience with model compression, quantization, pruning, edge inference frameworks, and performance profiling.
• Experience deploying ML models to production on mobile or embedded platforms and understanding mobile and embedded hardware architectures.
• Applicants must be authorized to work in the United States; U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. New H-1B visa petitions cannot be sponsored.

Nice to have

• Experience with custom NPU or DSP toolchains.
• Federated learning or on-device personalization experience.
• Safety-critical or industrial edge deployment experience.
• Open-source contributions to edge AI frameworks.
• Experience optimizing LLMs for on-device inference.

Culture & Benefits

• Full-time direct W2 employment.
• Work remotely within the United States.
• Opportunity to work on production edge AI systems across mobile and embedded platforms.
• Equal employment opportunity workplace.