Software Engineer (SDS Core, Evaluation)
Posted Updated
- The Data and Test Flywheel Engineer will be a key member of Applied Intuition’s data flywheel initiative — 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 sits at the intersection of large-scale data engineering and machine learning infrastructure
- You’ll work closely with ML engineers and system developers to automate data selection, curation, and model iteration so our vehicles can self-improve with minimal human intervention
- Build and maintain large-scale data processing pipelines (ETL) for ingesting and curating 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 across iterations
- Develop the core infrastructure that closes the loop between real-world test results and new model deployments
- Use your engineering expertise to help Applied Intuition’s vehicles learn from data at scale, improving safety and performance
- Mentor junior engineers and contribute to defining best practices for data-centric development
- Experience working with large-scale datasets and understanding data-driven development cycles
- Bachelor’s or higher degree in Engineering such as Computer Science, Electrical Engineering, Software Engineering
- Proficiency in Python and strong knowledge of data frameworks (Spark, Airflow, Kafka, etc.)
- Familiarity with machine learning workflows or model training/deployment, especially automation of those processes
- 3–5 years of experience in software or data infrastructure engineering
- Strong systems thinking and ability to work across multiple parts of the stack (data, infra, and ML)
- Interest in seeing the direct impact of your infrastructure work on how vehicles perform and improve
- Expertise in building and scaling data pipelines, distributed systems, or ML infrastructure
- 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
- Experience with highly automated ML training workflows
- Prior contributions to systems that connect data-driven model iteration loops (“data flywheel”)
- Previous work on ML platforms for large-scale products (e.g., Ads, Recommendation, or Autonomy pipelines)
- Ability to move fast, learn quickly, and mentor others while growing with the team