Software Engineer - AI SysML, Meta Superintelligence Labs

Meta • Menlo Park, CA

33d

About The Position

Meta’s MSL Airstore team is seeking a Software Engineer to lead the development of next-generation GenAI dataloading and storage systems. The ideal candidate will have experience in designing and scaling data infrastructure for AI/ML applications, with a focus on enabling efficient ingestion, transformation, data loading, and storage of massive datasets powering GenAI models. You will help drive technical direction, collaborate across functions, and shape the future of Meta’s AI data platforms.

Requirements

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• Demonstrated experience as a technical leader in the design and architecture of large-scale data infrastructure or storage systems
• Experience driving cross-functional engineering efforts and influence architectural direction without direct management responsibilities
• Track record of planning and executing technical roadmaps, with shorter-term projects laddering to long-term vision
• Experience with distributed systems and large-scale data management
• Experience mentoring and influencing engineers across organizations
• Specialized experience in one or more of the following domains. Data infrastructure for AI/ML (GenAI, LLMs, multimodal models), Distributed storage systems, data lakes, or cloud object stores, High-performance data pipelines and ETL frameworks, or Planet scale data base / data store
• Proficiency in C/C++, Python, or similar languages for developing data infrastructure
• Experience developing and optimizing data systems for AI/ML workloads

Nice To Haves

• Familiarity with modern data storage formats (e.g., Parquet, ORC) and data lake architectures
• Experience with Meta’s internal data infrastructure (Airstore, Scuba, Presto, etc.) is a plus

Responsibilities

• Serve as a technical leader for the design and architecture of scalable dataloading and storage solutions for GenAI workloads within WS Airstore
• Drive architectural decisions and set technical direction for high-throughput, low-latency data pipelines supporting large language and multimodal models
• Develop and optimize data storage formats, access patterns, and caching strategies for GenAI use cases
• Collaborate with research, infrastructure, and product teams to understand evolving GenAI data requirements and translate them into robust engineering solutions
• Define use cases, develop methodologies, and establish benchmarks to evaluate and improve data infrastructure approaches
• Mentor and provide technical guidance to engineers across the organization, fostering best practices in large-scale data engineering and distributed systems
• Stay abreast of industry and Meta-wide trends in AI data infrastructure, storage technologies, and distributed computing

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level