Senior Edge AI Engineer - Vehicle Health & Predictive AI

Sonatus; San Jose (CA); Hybrid; USD 227,000 - 300,000; Full time

Benefits offered by this job

Health care plan

401k retirement plan

Unlimited paid time off

Hybrid office work arrangement

Lunches on site

Phone & Internet reimbursement

Computer Accessory Allowance

Job summary

Sonatus is seeking a Senior Staff AI Engineer to lead Edge AI development for in-vehicle health monitoring. You will own end-to-end ML pipelines, from data ingestion to deployment on resource-constrained edge devices.

You will collaborate with AI and vehicle software teams, experiment with advanced models, and optimize for RAM/Flash budgets while working in a fast-paced startup environment. Hybrid role in Sunnyvale, CA.

Qualifications

• Bachelor's degree in CS, EE, or related field.
• 10+ years in ML engineering with 3+ years in Edge AI or embedded systems.
• Proven mentoring experience for junior engineers.
• Expert Python and strong C++ (14/17) for inference.
• Deep proficiency with PyTorch or TensorFlow; experience with ONNX/TFLite/TVM.

Responsibilities

• Build and train edge AI models (Transformers, LLMs, CNNs, LSTMs) for in-vehicle data.
• Integrate ML flows with cloud-based LLM APIs and synthetic data generation.
• Develop algorithms to detect software regressions and anomalies in logs and CAN data.
• Port and optimize models for CPU/GPU/embedded NPUs with memory optimization.
• Lead edge ML pipeline architecture and mentor junior engineers.

Skills

Python

C++ (modern)

Deep Learning

PyTorch

TensorFlow

Edge AI

MLOps

Mentoring

Education

Bachelor's degree in Computer Science / Electrical Engineering

Tools

PyTorch

TensorFlow

ONNX

TFLite

TVM

Job description

Sonatus is seeking a Senior Staff AI Engineer to lead Edge AI development for in-vehicle health monitoring. You will own end-to-end ML pipelines, from data ingestion to deployment on resource-constrained edge devices.

You will collaborate with AI and vehicle software teams, experiment with advanced models, and optimize for RAM/Flash budgets while working in a fast-paced startup environment. Hybrid role in Sunnyvale, CA.