Software Engineer - Data Infrastructure

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