Machine Learning Infrastructure Engineer

Request Highlights:
• Client Reality Labs (RL) Sensors Team is helping build novel products in Augmented and Virtual Reality. Client AR/VR research and development in Sensors and Sensing Systems is driving the state-of-the-art forward through relentless innovation. Our team explores, develops, and delivers new cutting-edge technologies that serve as the foundation of current and future AR/VR products at Client.
• We are looking for candidates with experience in software engineering with a deep understanding of software infrastructure and machine learning (ML) systems. This role will focus on designing and implementing systems to support ML development for sensor systems.
• Demonstrate a deep understanding of DevOps practices and apply them to ML operations.
• Handle the complexities of designing and implementing ML infrastructure systems in a dynamic and fast-paced environment.
• Contribute to the overall impact of the team by delivering robust and efficient ML infrastructure.

Summary:
Client Reality Labs (RL) Sensors Team is helping build novel products in Augmented and Virtual Reality. Client AR/VR research and development in Sensors and Sensing Systems is driving the state-of-the-art forward through relentless innovation. Our team explores, develops, and delivers new cutting-edge technologies that serve as the foundation of current and future AR/VR products at Client. We are looking for candidates with experience in software engineering with a deep understanding of software infrastructure and machine learning (ML) systems. This role will focus on designing and implementing systems to support ML development for sensor systems.

Responsibilities:
• Design and develop systems to support Machine Learning algorithm development within the team.
• Own the system design that will cater to multi-modal input, quick prototyping of algorithms, visualization tools and state-of-the-art ML algorithm architecture development.
• Build distributed systems and pipelines for data management, ensuring scalability, reliability, and performance.
• Demonstrate a deep understanding of DevOps practices and apply them to ML operations.
• Handle the complexities of designing and implementing ML infrastructure systems in a dynamic and fast-paced environment.
• Contribute to the overall impact of the team by delivering robust and efficient ML infrastructure.

Minimum Qualifications
• Bachelor's degree in Computer Science or a related field.
• Minimum 5+ years of experience in software engineering, with a focus on infrastructure design.
• 5+ years’ experience in Python and C++.
• Proven experience in designing complex systems and strong software engineering skills.
• Strong understanding and experience with distributed systems and infrastructure design.
• Demonstrated expertise in DevOps practices, with a focus on ML.

Preferred Qualifications
• Experience with ML pipeline automation and data management in ML workflows.
• Previous experience building ML systems and working on ML adjacent teams.
• Demonstrated experience in cross-group and cross-culture collaboration.
• Familiarity with the emerging Augmented Reality and Virtual Reality technologies.

Must-Have Skills:
• Minimum 5+ years of experience in software engineering, with a focus on infrastructure design.
• 5+ years experience in Python and C++.
• Proven experience in designing complex systems and strong software engineering skills.

Good-to-Have Skills:
• Strong understanding and experience with distributed systems and infrastructure design.
• Demonstrated expertise in DevOps practices, with a focus on ML.