Job Description
📋 Description Build and maintain large-scale data processing pipelines (ETL) for driving datasets. Design and implement systems that automate data selection, labeling, training, and testing loops. Collaborate with modeling teams to improve training efficiency and model performance. Develop infrastructure that closes the loop between real-world results and new model deployments. Apply engineering expertise to help vehicles learn from data at scale, improving safety. Mentor junior engineers and define best practices for data-centric development. 🎯 Requirements Bachelor's or higher degree in Engineering such as Computer Science, Electrical Engineering, Software Engineering 3–5 years in software or data infrastructure engineering Expertise in building and scaling data pipelines, distributed systems, or ML infrastructure Proficiency in Python and data frameworks (Spark, Airflow, Kafka, etc.) Experience with large-scale datasets and data-driven development cycles Familiarity with ML workflows or model training/deployment, especially automation 🎁 Benefits Health, dental, vision, life and disability insurance 401k with employer match Learning and wellness stipends Paid time off
