Software Engineer - Data Infrastructure at Luma AI

About the Role As a Data Infrastructure Engineer in Research at Luma, you will play a critical role in building and scaling the data infrastructure that supports our cutting-edge multimodal AI systems. Your work will focus on developing high-throughput, large-scale data processing pipelines tailored for machine learning research and internal ML platform needs. You will collaborate closely with ML researchers and product teams to create reliable, efficient, and easy-to-use data infrastructure that empowers innovation and accelerates development. This role requires a strong foundation in distributed systems and data engineering, with an emphasis on supporting complex machine learning workflows rather than traditional product data infrastructure.   Responsibilities - Build and maintain scalable data infrastructure for high-throughput machine learning workflows - Collaborate with ML researchers and product teams to ensure data systems meet evolving needs - Develop and optimize large-scale data pipelines and batch processing jobs - Contribute to the architecture and implementation of reliable, high-performance data platforms - Integrate open-source tools and continuously improve data infrastructure through monitoring and tuning - Participate in cross-functional projects to improve data reliability, scalability, and operational excellence - Support the evaluation and adoption of new programming languages and frameworks relevant to data infrastructure - Engage in continuous improvement of data infrastructure through monitoring, troubleshooting, and performance tuning - Collaborate with research & engineering teams to help define and refine best practices for data infrastructure development   Qualifications - Proficiency in Python (or similar languages with willingness to learn Python) and experience with large-scale, high-throughput data infrastructure - Familiarity with distributed computing frameworks (e.g., Ray, Spark, Beam) - Ability to design and optimize data pipelines for ML research and internal teams - Strong problem-solving skills and understanding of data engineering at scale - Collaborative, product-focused mindset; comfortable in fast-paced environments - Experience sourcing, integrating, and optimizing data from diverse and large datasets - Comfortable working in a fast-paced, product-focused environment with a strong execution mindset - Open to candidates across seniority levels, from mid-level individual contributors to senior engineers and managers.   Nice to have - Prior experience working with complex data infrastructure or AI/ML platforms highly desirable - Experience with open source data infrastructure projects is a plus - Experience working in the robotics industry preferred