AI Software Engineer

Pebble•Fremont, CA

21h•Onsite

About The Position

Join our SW team to build intelligent systems that power our electric vehicle platform. As a new grad or early-career engineer, you’ll develop AI agents for data analysis, automation, and user interaction while working with cutting-edge technology in the sustainable transportation space. This is a hands-on role where you’ll grow quickly, collaborate with experienced engineers, and see your work ship to production vehicles.

Requirements

0–2 years of experience building or experimenting with AI/ML systems (internships, research, coursework, or personal projects all count).
Bachelor’s (or currently completing a degree) in Computer Science, Machine Learning, or a related field.
Demonstrated curiosity and initiative in AI/ML through projects, competitions, or open-source contributions.
Familiarity with PyTorch, TensorFlow, Hugging Face, LangChain, or similar frameworks.
Solid Python fundamentals.
Exposure to databases, data pipelines, or time series data.
Basic understanding of RESTful APIs and cloud platforms (AWS, GCP).
Large Language Models (LLMs) and prompt engineering.
Retrieval-augmented generation (RAG) and vector databases.
Agent orchestration and workflow automation.

Nice To Haves

Internship or research experience in automotive, IoT, or hardware industries.
Exposure to vehicle telemetry, CAN protocols, or embedded systems data.
Real-time data processing or edge computing projects.
Data privacy, security, and compliance knowledge.

Responsibilities

Build and contribute to AI agents that analyze vehicle telemetry and sensor data.
Support development of predictive models for vehicle performance, battery health, and maintenance scheduling.
Help create pattern recognition systems for fleet monitoring and optimization.
Contribute to scalable data processing pipelines for production vehicle data.
Help develop intelligent data migration and ETL systems with built-in validation.
Build automated database ingestion agents that parse and structure complex datasets.
Contribute to AI-powered data visualization tools that generate insights automatically.
Develop AI agents for internal tools (documentation, quality tracking, process automation).
Support customer-facing AI systems for vehicle support and diagnostics.
Work on multi-modal AI agents handling text, voice, and visual inputs.
Integrate AI solutions with existing software infrastructure.
Deploy and maintain AI agents in production environments.
Collaborate with engineering teams on AI-enabled vehicle features.
Monitor and optimize AI system performance at scale.