Member of Technical Staff - Engineering Lead, Compute Platform

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 keeps our compute layer healthy and highly available. We run a Kubernetes-based platform distributed across multiple neo-clouds, where multi-cloud scheduling, node health, and performance debugging at scale present genuinely hard systems problems.

As Compute Platform Lead, you'll provide front-line leadership of the team that builds and operates this layer. You'll build, mentor, and grow a team of strong systems engineers, guide the technical and architectural decisions across multi-cloud scheduling, cluster management, and next-generation GPU deployments, and work closely with our training teams to co-design fault tolerance, node health checks, and remediation. You'll stay close enough to the systems to make targeted contributions as an individual contributor and to maintain a deep understanding of the compute fleet our largest training runs depend on. Managing vendors — and the important deals that come with them — is a core part of the job.

WHAT YOU'LL DO

• Build, mentor, and grow a high-performing team of systems engineers. Coach and support your reports in understanding, and pursuing, their professional growth.
• Provide front-line leadership of engineering efforts to keep the compute fleet reliable and highly available — multi-cloud scheduling, cluster management, and the path to next-generation GPUs and increasingly larger cluster sizes.
• Stay hands-on: become familiar with the team's technical stack enough to make targeted contributions as an individual contributor.
• Manage day-to-day execution: prioritize the team's work and manage projects in a highly dynamic, fast-paced environment.
• Guide technical and architectural decisions, emphasizing scalability, robustness, and reliability — automatic remediation, topology-aware scheduling, capacity planning, rapid hardware debugging, and cluster-wide monitoring and performance benchmarking.
• Work closely with our training teams to co-design fault tolerance, node health checks, and remediation, and manage the vendor relationships and important deals the compute fleet depends on.
• Prepare the fleet for what's next: next-generation GPUs and larger clusters, and — longer term — multi-cloud storage, petabyte-scale data replication, and GPU-to-GPU network performance.
• Raise the bar for technical judgment, prioritization, communication, and execution in a fast-moving environment.

WHAT WE'RE LOOKING FOR

• Experience building, mentoring, and growing systems or infrastructure teams while staying technically hands-on. (Comfortable growing into leading a team of ~10 quickly if you haven't managed at that scale before.)
• Deep systems-level engineering experience with a focus on cluster-wide behavior and maintenance.
• Strong coding ability and the credibility to earn the technical trust of a strong team.
• Depth in at least one of orchestration, storage, or GPU hardware — with the ability to learn the rest. Deep GPU knowledge beyond standard Kubernetes (e.g., NCCL) is a plus, not a prerequisite.
• Alignment with a Kubernetes-first architecture.
• Cloud storage expertise — managing high-performance data products (like VAST) across multiple data centers and handling datasets and checkpointing at scale — is a plus.
• Experience managing vendors, including negotiating and operating important deals.
• Ability to guide strategy and drive execution across a multi-cloud, large-fleet environment, and to partner effectively with research and training teams.

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.

Equal Employment Opportunity Statement
Reflection AI is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), sexual orientation, gender identity or expression, national origin, ancestry, age, marital status, disability, genetic information, veteran or military status, or any other characteristic protected by applicable law. We encourage applicants from all backgrounds to apply.

We provide reasonable accommodations throughout the hiring process for applicants with disabilities, pregnancy-related limitations, or religious needs. If you need an accommodation, contact us at [email protected].

We will consider for employment qualified applicants with arrest and conviction records in accordance with applicable law, including the San Francisco Fair Chance Ordinance and the California Fair Chance Act.

Candidate and Employee Privacy Notice: We collect and process personal data about applicants for the purposes described in our Candidate and Employee Privacy Notice