Edge AI Engineer, Self-Aware Vehicle Health

Sonatus; Sunnyvale (CA); Hybrid; USD 198,000 - 272,000; Full time

Benefits offered by this job

Health benefits

Hybrid office work arrangement

401k

Lunches on-site

Paid time off

Job summary

Sonatus, a leader in AI-enabled automotive software, seeks a Staff AI Engineer to drive Edge AI for in-vehicle health monitoring. You will build and deploy models analyzing logs, CAN signals, and multi-modal data to detect and predict subsystem health in real-time.

Own end-to-end ML pipeline from data ingestion to deployment on resource-constrained devices. You will lead architecture, collaborate with AI and vehicle software experts, and optimize models for embedded hardware.

Qualifications

• Bachelor’s degree in Computer Science, Electrical Engineering, Software Engineering, or a related field.
• 7+ years in Machine Learning Engineering, with 3+ years focused on Edge AI or Embedded Systems.
• Proven experience mentoring junior engineers in software development.
• Expert Python (for training) and decent working knowledge of modern C++ (C++14/17 for inference).
• Deep proficiency with PyTorch or TensorFlow, and experience with inference engines like ONNX, TFLite, or TVM.
• Experience with NLP techniques for textual data parsing, sequence modeling (RNN/GRU), vector store, or lightweight LLMs/SLMs.
• Experience with libraries like scikit-learn, tslearn, or statsmodels for anomaly detection on sensor data.
• Proven ability to lead technical projects from concept to production in an ambiguous, fast-paced environment.

Responsibilities

• Build and train AI Edge models to process logs and multi-modal data.
• Integrate ML flows with cloud-based LLM APIs and synthetic data.
• Develop algorithms to cluster log patterns and detect regressions or crashes.
• Design time-series models to monitor CAN bus and sensor data.
• Correlate signal anomalies with system events to identify root causes.
• Port and optimize PyTorch/TensorFlow models for CPU/GPU/embedded targets.
• Apply quantization, pruning, distillation for memory budgets.
• Define on-device data filtering strategy for local vs cloud processing.
• Lead the edge ML pipeline architecture and mentor junior engineers.

Skills

Python

C++ (C++14/17)

PyTorch

TensorFlow

Edge AI

NLP

Anomaly detection

Leadership

CAN/LAN bus knowledge

ONNX

TFLite

TVM

NVIDIA TensorRT

Qualcomm SNPE

Linux/QNX debugging

Education

MS/PhD in CS/Engineering

Bachelor's degree in a related field

Tools

ONNX

TFLite

TVM

NVIDIA TensorRT

Qualcomm SNPE

Job description

Sonatus, a leader in AI-enabled automotive software, seeks a Staff AI Engineer to drive Edge AI for in-vehicle health monitoring. You will build and deploy models analyzing logs, CAN signals, and multi-modal data to detect and predict subsystem health in real-time.

Own end-to-end ML pipeline from data ingestion to deployment on resource-constrained devices. You will lead architecture, collaborate with AI and vehicle software experts, and optimize models for embedded hardware.