Staff AI Engineer (Edge AI)

Location: Sunnyvale, California, United States; hybrid role with three days per week in the office

Salary: $197,500–$272,000 USD base salary per year

Company

hirify.global develops software and AI technologies for software-defined vehicles, with solutions deployed across more than 8 million vehicles.

What you will do

• Build and train Edge AI models, including Transformers, LLMs, CNNs, LSTMs, tree-based models, autoencoders, and Isolation Forests.
• Own the end-to-end ML pipeline from data ingestion and training to deployment on resource-constrained edge devices.
• Process application logs, kernel traces, CAN-bus data, onboard sensor signals, and other multimodal vehicle data.
• Develop anomaly detection, clustering, regression detection, and root-cause correlation for vehicle software and subsystem health.
• Port and optimize PyTorch and TensorFlow models for CPU, GPU, and embedded NPU targets using quantization, pruning, distillation, and memory optimization.
• Lead edge ML architecture, define on-device versus cloud processing, and mentor junior engineers.

Requirements

• Bachelor’s degree in Computer Science, Electrical Engineering, Software Engineering, or a related field.
• 7+ years of Machine Learning Engineering experience, including 3+ years focused on Edge AI or embedded systems.
• Expert Python and working knowledge of modern C++14/17 for inference.
• Deep proficiency with PyTorch or TensorFlow and inference engines such as ONNX, TFLite, or TVM.
• Experience with NLP, sequence modeling, vector stores or lightweight LLMs, plus anomaly detection for sensor time-series data.
• Experience deploying to ARM-based edge environments, managing memory manually, and working with limited compute resources; proven technical leadership and mentoring experience.

Nice to have

• MS or PhD in Computer Science, Engineering, or a related field.
• Automotive Edge systems and formats such as CAN, DBC, UDS, SOME/IP, or MQTT.
• Linux or QNX kernel logs, process states, and operating-system debugging.
• Computer Vision or ADAS experience.
• NVIDIA TensorRT or Qualcomm SNPE.

Culture & Benefits

• Fast-paced startup environment with direct impact on fleet reliability and production vehicle systems.
• Medical, dental, and vision coverage.
• 401(k) retirement plan, life insurance, and flexible dependent-care benefits.
• Unlimited paid time off and 14+ paid holidays.
• Hybrid office arrangement with complimentary on-site meals, wellness allowance, phone and internet reimbursement, and computer accessory allowance.