Data & ML Pipeline Software Engineer

Responsibilities

• 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
• Mentor junior engineers and contribute to defining best practices for data-centric development

Requirements

• Bachelor's or higher degree in Computer Science, Electrical Engineering, or Software Engineering
• 3–5 years of experience in software or data infrastructure engineering
• Expertise in building and scaling data pipelines, distributed systems, or ML infrastructure
• Proficiency in Python
• Strong knowledge of data frameworks such as Spark, Airflow, or Kafka
• Experience working with large-scale datasets and data-driven development cycles
• Familiarity with machine learning workflows or model training/deployment automation

Preferred Qualifications

• Experience with automotive (AV) or robotics systems
• Previous work on ML platforms for large-scale products
• Experience with highly automated ML training workflows
• Prior contributions to systems that connect data-driven model iteration loops

About the Company

Applied Intuition is powering the future of physical AI, creating the digital infrastructure needed to bring intelligence to every moving machine on the planet, servicing the automotive, defense, trucking, construction, mining, and agriculture industries.