Machine Learning Infrastructure Developer

• Create robust, flexible, and scalable machine learning tooling and infrastructure that supports research scientists in leveraging large-scale internal infrastructure (e.g., source control, distributed compute clusters, data storage).
• Work collaboratively as part of a multifunctional team where communication, documentation, and teamwork are highly valued.
• Write clean, maintainable code and debug complex problems that span multiple systems.
• Coordinate with a large set of internal infrastructure and tooling teams to evaluate and integrate existing systems.
• Learn continuously, explore unfamiliar technologies, and embrace ambiguity when solving complex AR/VR and research-driven problems.

• Bachelor's degree in Computer Science or a related field, or equivalent work experience.
• 4+ years of industry experience writing Python-based software for machine learning and data systems.
• Strong Python engineering skills with a focus on building and maintaining scalable infrastructure.
• Hands-on experience with PyTorch or similar machine learning frameworks (e.g., TensorFlow).
• Experience working with distributed systems or high-performance compute infrastructure.
• 2+ years of experience working with large, complex datasets for machine learning, including data capture and annotation.
• Demonstrated experience implementing and evaluating end-to-end machine learning systems or prototypes.
• Experience with deployment workflows and continuous integration pipelines.

Good to Have

• Experience working with complex, real-world multimodal datasets.
• Audio-related machine learning or signal processing experience.
• Experience collaborating closely with research users or internal customers to deliver robust, stable, and scalable tooling.
• Experience writing scalable ML pipelines or tooling used by research teams.
• Familiarity with Linux or Windows shell scripting.