Staff AI Engineer, Data Analytics & Modeling - Office of the CTO

Sonatus•Sunnyvale, CA

2d•$1 - $10•Hybrid

About The Position

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 6 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. The Opportunity: Sonatus is seeking a highly motivated Staff AI Engineer with expertise in data analytics and modeling to build AI-based software for next-generation AI-driven software-defined vehicles. You will be critical in accelerating software innovations that solve complex, real-world customer problems.

Requirements

In-depth theoretical and practical knowledge of a wide range of Data Science and Machine Learning algorithms, including Deep Learning (e.g., CNNs, RNNs, Transformers) and Reinforcement Learning.
Strong Python programming skills with extensive experience using data analysis and ML frameworks and libraries.
Proven experience in designing, training, tuning, and evaluating diverse machine learning models, including LLMs, computer vision, and time series analysis.
Expertise in data preprocessing, feature engineering, and advanced model evaluation techniques (e.g., A/B testing, causal inference).

Nice To Haves

Master’s or PhD in a Science or Engineering field.
Experience in building and maintaining scalable, big data applications in a cloud environment.

Responsibilities

Lead end-to-end data exploration, analytics, and modeling on large-scale, multi-source data to uncover insights and drive business outcomes.
Architect, design, develop, and deploy optimized data analytics algorithms, models, and solutions.
Drive the development of agentic AI applications leveraging data processing and analytics pipelines.