Software Engineer (SDS Core, Data and Test Flywheel)

Join Applied Intuition as a Data & ML Pipeline Software Engineer, where you'll play a crucial role in building the systems that connect vehicle data collection, training, and automated model improvement. You'll create the infrastructure that allows our autonomous driving stack to continuously learn from real-world and simulation data, accelerating development across teams working on perception, planning, and control. This role requires expertise in building and scaling data pipelines, distributed systems, or ML infrastructure, and offers a range of benefits including health insurance, a fitness stipend, 401(k) match, and more.

• Construire et maintenir des pipelines de traitement de données à grande échelle (ETL) pour l'ingestion et la curation des ensembles de données de conduite.
• Collaborer avec les équipes de modélisation pour améliorer l'efficacité de l'entraînement et la performance des modèles à travers les itérations.
• Utiliser votre expertise en ingénierie pour aider les véhicules d'Applied Intuition à apprendre des données à grande échelle, améliorant ainsi la sécurité et la performance.
• Experience working with large-scale datasets and understanding data-driven development cycles
• Familiarity with machine learning workflows or model training/deployment, especially automation of those processes
• Interest in seeing the direct impact of your infrastructure work on how vehicles perform and improve
• Bachelor's or higher degree in Engineering such as Computer Science, Electrical Engineering, Software Engineering
• Expertise in building and scaling data pipelines, distributed systems, or ML infrastructure
• Strong systems thinking and ability to work across multiple parts of the stack (data, infra, and ML)
• 3–5 years of experience in software or data infrastructure engineering
• Proficiency in Python and strong knowledge of data frameworks (Spark, Airflow, Kafka, etc.)
• Prior contributions to systems that connect data-driven model iteration loops (“data flywheel”)
• Don’t meet every single requirement? If you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles
• Experience with automotive (AV) or robotics systems
• Ability to move fast, learn quickly, and mentor others while growing with the team
• Experience with highly automated ML training workflows
• Previous work on ML platforms for large-scale products (e.g., Ads, Recommendation, or Autonomy pipelines)