Job description

OUR MISSION Reflection is a research lab making intelligence open and accessible for everyone to use, customize, and build on. We build open models that let anyone control their intelligence and help shape the future of AI. Our mission: make intelligence open and accessible to all. ABOUT THE ROLE Reflection’s Compute Platform team specializes in keeping our compute layer healthy and highly available. We run a K8s-based platform distributed across multiple neo-clouds. We manage multi-cloud scheduling, node health, and performance debugging at this scale presents genuinely hard systems problems. More broadly, you will work closely with Reflection's training teams to co-design fault tolerance, node health checks, and remediation strategies. WHAT YOU’LL DO - Cluster Management: Build and maintain tools for the automatic remediation, topology-aware scheduling, capacity planning and rapid hardware debugging. - Platform Engineering: Design and iterate on our cluster management stack for workloads across large, multi-GPU fleets - Monitoring & Observability: Implement comprehensive cluster-wide monitoring, focusing on durability and active performance benchmarking. - Roadmap Execution: Prepare the infrastructure for next-generation GPU deployments and increasingly larger cluster sizes. Long-term, you will help own multi-cloud storage, petabyte-scale data replication, and GPU-to-GPU network performance. WHAT WE’RE LOOKING FOR • Systems-level engineering experience with a focus on cluster-wide behavior and maintenance. • Strong coding ability and a demonstrated focus on systems or GPU infrastructure. • Deep GPU hardware knowledge beyond standard Kubernetes,e.g., familiarity with NCCL. • Alignment with a K8s-first architecture • Cloud storage expertise, specifically managing high-performance data products (like VAST) across multiple data centers, connecting those storage environments together and handling datasets and checkpointing at scale. WHAT WE OFFER: We believe that to make intelligence open and accessible to all, you need to start at the foundation. Joining Reflection means building from the ground up as part of a talent-dense team. You will help define our future as a company, and help define the future of open foundational models. We want you to do the most impactful work of your career with the confidence that you and the people you care about most are supported. - Top-tier compensation: Salary and equity structured to recognize and retain our talent globally. - Stock options: Everyone who joins and contributes to Reflection's success gets to share in the upside through stock options. - Health & wellness: Comprehensive medical, dental, vision, and life, with an annual wellness allowance. - Meals: Lunch and dinner are provided in the office daily. - Life & family: 22 weeks paid parental leave for all new birthing and non-birthing parents, including adoptive and surrogate journeys. - Vacation days: Unlimited paid time off in the U.S. and 30 days in the U.K. - Sponsorship support: We sponsor visas to help exceptional talent join our team and support long-term immigration pathways where applicable. - Team building: We have regular off-sites, happy hours, and team celebrations. Export Control Notice: This position may require access to technology or source code subject to the U.S. Export Administration Regulations. Any offer of employment for this role may be conditioned on the Company's ability to provide the candidate with access to such technology or source code in compliance with applicable U.S. export control laws, which may require the Company to seek government authorization. Candidate and Employee Privacy Notice: We collect and process personal data about applicants for the purposes described in our Candidate and Employee Privacy Notice cdn.sanity.io

Requirements

Must-haves

Cluster Management: Build and maintain tools for the automatic remediation, topology-aware scheduling, capacity planning and rapid hardware debugging.
Platform Engineering: Design and iterate on our cluster management stack for workloads across large, multi-GPU fleets
Monitoring & Observability: Implement comprehensive cluster-wide monitoring, focusing on durability and active performance benchmarking.
Systems-level engineering experience with a focus on cluster-wide behavior and maintenance.
Strong coding ability and a demonstrated focus on systems or GPU infrastructure.
Deep GPU hardware knowledge beyond standard Kubernetes,e.g., familiarity with NCCL.
Alignment with a K8s-first architecture
Cloud storage expertise, specifically managing high-performance data products (like VAST) across multiple data centers, connecting those storage environments together and handling datasets and checkpointing at scale.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aikubernetes

Platform: ashby
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

Paid Time Off

Parental Leave

Wellness