Data & ML Pipeline Engineer for Autonomous Driving

Applied Intuition; Sunnyvale (CA); On-site; USD 125,000 - 222,000; Full time

Benefits offered by this job

Equity options

Comprehensive health benefits

401k retirement benefits with employer match

Job summary

Applied Intuition is hiring a Data and Test Flywheel Engineer in Sunnyvale, California. In this role, you will help build systems that connect vehicle data and improve autonomous driving capabilities. Your expertise in data pipelines and machine learning infrastructure will be crucial for the development process.

The position requires a Bachelor's degree in Engineering and substantial experience in software or data infrastructure. You will work closely with ML engineers, focusing on automating data processes and ensuring continual improvement.

Qualifications

• 3–5 years of experience in software or data infrastructure engineering.
• Familiarity with machine learning workflows or model training/deployment.
• Interest in seeing the direct impact of your infrastructure work.

Responsibilities

• Build and maintain large-scale data processing pipelines (ETL).
• Design and implement systems that automate data selection.
• Collaborate with modeling teams to improve training efficiency.

Skills

Building and scaling data pipelines

Distributed systems

Machine learning infrastructure

Proficiency in Python

Data frameworks (Spark, Airflow, Kafka)

Large-scale datasets

Systems thinking

Mentorship

Education

Bachelor's or higher degree in Engineering

Tools

Python

Spark

Airflow

Kafka

Job description

Applied Intuition is hiring a Data and Test Flywheel Engineer in Sunnyvale, California. In this role, you will help build systems that connect vehicle data and improve autonomous driving capabilities. Your expertise in data pipelines and machine learning infrastructure will be crucial for the development process.

The position requires a Bachelor's degree in Engineering and substantial experience in software or data infrastructure. You will work closely with ML engineers, focusing on automating data processes and ensuring continual improvement.