AI Software Engineer, New Graduate (In-Vehicle Log Analysis)
About The Position
Join a high-performing team at Sonatus that’s redefining what cars can do in the era of Software-Defined Vehicles (SDV). 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. That’s why leading OEMs trust Sonatus to accelerate this shift. Our technology is already in production across more than 5 million vehicles on the road today and rapidly expanding. 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. Join us and help redefine what’s possible as we shape the future of mobility. This role is ideal for an MSc or PhD student with a strong background in AI/ML model development. You will conduct research to evaluate and benchmark various model architectures for "low-training" or few-shot learning applications specifically for embedded vehicle logs. This a temporary role that runs for approximately 12 weeks with a projected start date in early June. Please note that we are only considering candidates who graduated in Spring 2026 and are local to the Bay Area, as this role follows a hybrid schedule with three in‑office days per week.
Requirements
- Must have graduated in Spring 2026 with a BS, MS, or PhD degree with a focus on AI/ML model development.
- AI/ML Expertise: Strong understanding of few-shot learning, neural architecture search, or anomaly detection.
- Technical Proficiency: Strong programming skills in Python and deep learning frameworks like PyTorch or TensorFlow.
- Prior experience with NLP and language models (e.g., SBERT).
- Must be local to the bay area, or willing to relocate, and come into office 3 days/week (Monday, Tuesday and Thursday).
Nice To Haves
- Experience with "low-training" applications in resource-constrained or embedded environments.
- Familiarity with automotive logs such as ADB or DLT.
Responsibilities
- Research & Benchmarking: Conduct an AI research study to identify efficient neural architectures for high-accuracy log analysis.
- Model Development: Develop and evaluate few-shot learning applications for embedded vehicle logs (e.g., ADB, DLT).
- Experimental Validation: Perform experimental validation of models in resource-constrained environments using internal compute unit data streams.
- Documentation: Clearly document findings, experiments, and results of various benchmarked architectures.
Benefits
- Complimentary lunches, snacks and beverages during on-site working days
- Hybrid office work arrangement
- Computer accessory allowance
- 15 paid holidays
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What This Job Offers
Career Level
Entry Level
