AI Engineer

AI Engineer Automotive Software Innovation (Sunnyvale, CA | Hybrid | $225K to $300K)

About the Company

A rapidly growing automotive technology company is revolutionizing the evolution of vehicles through software. Their AI-driven platform enables next-generation, software-defined vehicles, bridging the gap between automotive reliability and consumer-grade innovation. With technology already deployed in over 5 million vehicles worldwide, they are trusted by top global OEMs to power the future of connected mobility.

Role Overview

We are seeking a highly skilled AI Engineer with deep expertise in machine learning, data science, and model optimization. This is a hands-on role where you'll help design, implement, and deploy scalable AI models that enhance intelligent vehicle systems. You'll collaborate closely with cross-functional teams across data, embedded systems, and cloud infrastructure to deliver production-ready AI solutions.

Key Responsibilities

Design and develop AI/ML models using Python, TensorFlow, PyTorch, and ONNX.

Optimize model performance and deploy solutions across distributed automotive environments.

Collaborate with data and engineering teams to operationalize ML pipelines using MLOps best practices.

Conduct experiments, evaluate models, and iterate to ensure reliability, efficiency, and scalability.

Present solutions and technical insights to leadership and technical peers.

Requirements

Bachelors or Masters degree in Computer Science, AI/ML, or related field.

4+ years of experience in applied machine learning or AI engineering.

Strong proficiency in Python and experience with TensorFlow, PyTorch, or similar frameworks.

Solid understanding of data pipelines, MLOps, and model deployment.

Experience with real-time, embedded, or distributed systems is a strong plus.

Excellent communication skills and a collaborative, problem-solving mindset.

Location & Work Setup

Hybrid Sunnyvale, CA

Compensation

$225,000 $300,000 + competitive benefits

Interview Process

Recruiter Screening

Technical Interview (Python Coding)

Onsite Technical Presentation (Algorithms, ML, Data Science)

Final Interview with CTO

PyTorch TensorFlow Pipelines Scalability Algorithms Compensation Screening Data Science Reliability Optimization Machine Learning Communication Skills Infrastructure Computer Science Software Design Engineering Python Science Leadership Communication