Sonatus

Staff AI Engineer, Edge AI

Sunnyvale, CA · Staff+

Sponsorship not specified$198k-$272kDetected 7 days ago

PythonC++AlgorithmsVector DatabasesLinuxMachine LearningTensorFlowPyTorchscikit-learnNLPComputer VisionLLMsMLOpsElectrical EngineeringMentoring

About the role

That's why leading OEMs trust Sonatus to accelerate this shift.
Our technology is already in production across more than 8 million vehicles on the road today and rapidly expanding.
Join us and help redefine what's possible as we shape the future of mobility.

Build and train AI Edge models (e.g., Transformers, LLM, CNN, LSTM, Trees) to process unstructured application logs, kernel traces, and multi-modalities.
Develop algorithms to automatically cluster log patterns and detect software regressions, race conditions, or crash precursors.
Implement logic to correlate signal anomalies (e.g., ADAS drifts, sensor spikes, latency jitters) across different modalities with system events to identify root causes.
Port and optimize PyTorch/TensorFlow models into production-grade models for execution on CPU/GPU-bound targets or embedded NPUs.
Lead the architecture for the edge ML pipeline and mentor junior engineers on best practices for embedded AI.
You will own the end-to-end ML pipeline-from data ingestion and model training to deployment on resource-constrained edge devices and model optimization.
You will work in a fast-paced startup environment where your code will directly impact fleet reliability and build the next generation of the self-aware vehicle.

Bachelor's degree in Computer Science, Electrical Engineering, Software Engineering, or a related field.
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.
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.

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.
Sunnyvale HQ Benefits & Perks Offered:
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
We are looking for a great Staff AI Engineer to join our seasoned AI team and lead the development of Edge AI for in-vehicle self-aware health monitoring and prediction.
Design unsupervised and supervised learning models (e.g., Autoencoders, Isolation Forests) to monitor time-series data from CAN bus and on-board sensors.

At Sonatus, we're driving the transformation to AI-enabled software-defined vehicles.
Traditional automotive software methods can't keep pace with consumer expectations shaped by the mobile industry-where features evolve rapidly, update seamlessly, and improve continuously.
Headquartered in Sunnyvale, CA, with 250+ employees worldwide, Sonatus combines the agility of a fast-growing company with the scale and impact of an established partner.
Backed by strong funding and proven by global deployment, we're solving some of the most interesting and complex challenges in the industry.
Our solutions are already on the road with millions of vehicles, and we are quickly expanding our offerings for production-grade AI on the Edge.

This listing is sourced directly from Sonatus's careers page and normalized into a canonical job model.