Staff Machine Learning Engineer

The role

You will lead the development of Edge AI for in-vehicle self-aware health monitoring and prediction. You will build and deploy AI models that analyze continuous vehicle data to detect and predict subsystem health and failures in real time.

What you will do

• Build and train AI Edge models to process unstructured application logs, kernel traces and multi-modalities.
• Integrate ML flows, including cloud-based LLM APIs, with emphasis on synthetic data creation.
• Develop algorithms to automatically cluster log patterns and detect software regressions, race conditions, or crash precursors.
• Design unsupervised and supervised learning models to monitor time-series data from CAN bus and on-board sensors.
• Implement logic to correlate signal anomalies across different modalities with system events to identify root causes.
• Port and optimize pytorch/TensorFlow models for execution on CPU/GPU bound targets or embedded NPUs.
• Apply quantization, pruning, distillation and memory optimization for strict RAM/Flash budgets.
• Define the data strategy for on-device filtering.
• Lead the architecture for the edge ML pipeline and mentor junior engineers on best practices for embedded AI.

Required 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), 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.
• Ability to communicate with stakeholders and articulate trade-offs.
• Experience deploying to Edge environments (e.g. ARM based), managing memory manually, and working with limited compute resources.

Nice to have

• Strong Computer Vision (CV) track record
• MS/PhD in Computer Science, Engineering, or related fields.
• Familiarity with Edge systems and preferably automotive (CAN (DBC files), UDS, SOME/IP, or MQTT
• Understanding of Linux/QNX kernel logs (dmesg), process states, and OS-level debugging.
• Experience with NVIDIA TensorRT, Qualcomm SNPE.

About the company

Sonatus is a global leader in the automotive industry, providing key technologies that enable intelligent, software-defined vehicles. The company is headquartered in Sunnyvale, CA, with 250+ employees worldwide.