Software Engineer, ML Infrastructure, Reality Labs Research

Meta; Redmond, Seattle (WA, WA); On-site; USD 170,000 - 250,000; Full time

Job summary

Meta Reality Labs Research (RL-R) is seeking a senior software engineer to set the technical direction for our large-scale Kubernetes-based ML compute platform. You will drive reliability, scale, and efficiency, partnering across RL-R and engineering teams to turn evolving ML workload needs into concrete platform capabilities.

The role demands hands-on leadership, experience operating complex distributed systems in production, and collaboration to improve tooling, observability, and performance

Qualifications

• 8+ years of professional software engineering experience, including technical leadership of cross-team infrastructure.
• Experience building and maintaining production systems in Python, Go, C++, or similar languages.
• Proven ability to design, operate, and scale large distributed systems in production.
• Hands-on experience running Kubernetes at scale and using GPU/ML training infrastructure.
• Familiarity with HPC networking, storage, and high-performance networking concepts.

Responsibilities

• Set technical direction for the ML compute platform powering model training, inference, and rendering.
• Drive reliability, scale, and efficiency as demand grows; partner across teams to turn ML workload needs into platform capabilities.
• Elevate team practices through code reviews, design feedback, and knowledge sharing.

Skills

Software engineering

Technical leadership

Distributed systems

Kubernetes

Education

Bachelor's degree in Computer Science, Computer Engineering, relevant field

Tools

Kubernetes

PyTorch

NVIDIA DGX

Job description

Meta's mission is to give people the power to build community and bring the world closer together. Through our family of apps and services, we're building a different type of company that connects billions of people around the world, gives them ways to express what matters most to them, and helps bring people closer together. Whether we're creating new products or helping a small business expand its reach, people at Meta are builders at heart. Our global teams are constantly iterating, solving problems, and working to empower people around the world to build community and connect in meaningful ways.

Meta Reality Labs Research (RL-R)

At Meta Reality Labs Research (RL-R), our goal is to explore, innovate, and design novel interfaces and hardware subsystems for the next generation of virtual, augmented, and mixed reality experiences. Our research team has built and operates a shared ML compute platform: a large-scale, Kubernetes-based multi-use cluster that powers model training, inference, rendering, and unique research workloads with interactive development for research and engineering teams across RL-R. We are looking for a senior software engineer to set technical direction for this platform, driving its reliability, scale, and efficiency as demand grows, and partnering across teams to turn evolving ML workload needs into platform capabilities. In this role, you will be a hands-on technical leader who has experience navigating ambiguous problem spaces and driving them to concrete solutions, operates complex distributed systems in production, and elevates team practices through code reviews, design feedback, and knowledge sharing.

Meta is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, you may contact us at [e-mail]

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience8+ years of professional software engineering experience, including technical leadership of complex, cross-team infrastructure efforts
• Experience building and maintaining production systems in Python (and/or Go, C++, or a similar language)
• Proven experience designing, operating, and scaling large distributed systems in production, including production reliability / oncall ownership
• Hands-on experience running container orchestration (Kubernetes or comparable) at scale
• Experience with one or more of: GPU/ML training infrastructure, cluster/batch scheduling, distributed storage, or high-performance networking
• Demonstrated ability to drive ambiguous, organization-level technical problems to resolution and to set multi-quarter technical direction
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Large-scale distributed or parallel storage systems (e.g., HDFS, Isilon, Lustre)
• Deep Linux systems experience, performance tuning, and observability (metrics, tracing, alerting)
• GPU cluster operations (NVIDIA DGX, H100/A100), NCCL, and high-performance networking (InfiniBand / RoCE)
• Distributed ML training frameworks (e.g., PyTorch) and the surrounding training/inference stack
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Kubernetes operators/CRDs and batch schedulers (e.g., Volcano, Slurm, Kueue)
• Experience with Hack/PHP
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)