Software Engineer, ML Infrastructure, Reality Labs Research

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.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 accommodations-ext@fb.com

Software Engineer, ML Infrastructure, Reality Labs Research Responsibilities:

• Set technical direction for and lead the design, build, and operation of large-scale, multi-tenant GPU/ML training, inference, rendering, and general compute infrastructure on Kubernetes
• Drive cross-team and org-level initiatives that improve cluster reliability, scheduling efficiency, utilization, and scale, including datacenter and hardware migrations and expansions
• Our reliability for the cluster end to end: participate in and improve oncall and incident response, and build the automation and observability that reduces operational costs
• Define and drive best practices in system design, testing, code health, and operational excellence across the team
• Partner with research and infrastructure teams to translate ML workload requirements into platform capabilities, and influence architecture and technical decisions beyond your immediate team
• Mentor engineers, review designs, and improve the overall technical quality of the team's work through code reviews, design guidance, and knowledge sharing
  
  

Minimum Qualifications:

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• 8 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
  
  

Preferred Qualifications:

• 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)
  
  

About Meta:

Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.

Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.

Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.

$183,997/year to $257,000/year bonus equity benefits

Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.