Senior 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 vehicle data to detect and predict sub-system 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.
• 10+ 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 stores, 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) / ADAS track record
• MS/PhD in Computer Science, Engineering, or related fields.
• Familiarity with Edge systems and preferably automotive formats (CAN, DBC, UDS, SOME/IP, or MQTT.
• Understanding of Linux/QNX kernel logs (dmesg), process states, and OS-level debugging.
• Experience with NVIDIA TensorRT, Qualcomm SNPE.

Benefits

• Health care plan (Medical, Dental & Vision)
• Flexible and Dependent Care Expense program
• Retirement plan (401k)
• Life Insurance (Basic, Voluntary & AD&D)
• Unlimited paid time off per year, 14+ paid holidays
• Hybrid office work arrangement
• Complimentary lunches, snacks, and beverages during on-site working days
• Wellness benefit allowance
• Phone & Internet reimbursement
• Computer Accessory Allowance

About the company

Sonatus is a global leader in the automotive industry, providing key technologies that enable intelligent AI-defined vehicles. Headquartered in Sunnyvale, CA, with 250+ employees worldwide, the company's technology is in production across more than 9 million vehicles.