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Software Engineer, Systems & ML Infrastructure - MSL FAIR Foundations

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Key skills for this role

PythonC++

Design, build, and operate scalable infrastructure for running evaluations across large model fleets, datasets, modalities, and compute environments
Develop orchestration, scheduling, data, and artifact-management systems that make the evaluation workflows reliable and reproducible
Build APIs, abstractions, and developer tools that allow researchers to launch, debug, compare, and interpret evaluations efficiently
Improve system reliability through testing, observability, capacity planning, performance optimization, and automated failure recovery
Partner with research and engineering teams to translate new evaluation requirements into reusable platform capabilities

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
3+ years of software engineering experience in building backend, distributed, data, or machine learning infrastructure
Proficiency in Python, C++, or another systems programming language
Experience designing, implementing, and operating reliable services, platforms, or data-processing systems
Experience independently delivering medium- to large-scale technical projects from design through production operation
Demonstrated knowledge of software engineering practices, including testing, code review, observability, incident response, and performance analysis
Ability to work effectively with researchers and engineers and to adapt to rapidly changing requirements

Experience building infrastructure for large-scale machine learning training, inference, evaluation, or data processing
Experience with distributed compute systems, workflow orchestration, containers, cluster schedulers, or cloud infrastructure

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