High Performance Computing Engineer

• Design, operate, and maintain large-scale HPC environments, drawing on hands-on engineering experience in production settings.
• Own the deployment, configuration, and day-to-day operation of HPC schedulers (e.g., SLURM, Kubernetes), ensuring reliable and efficient job scheduling at scale.
• Serve as a technical owner for at least one core HPC domain (GPU compute, high-performance storage, networking, or similar), including ongoing maintenance, performance tuning, and troubleshooting of massive clusters.
• Develop and maintain automation and tooling using Bash and/or Python to improve cluster reliability, observability, and operational efficiency.
• Partner closely with researchers and engineers to support their workloads, troubleshoot cluster usage issues, and triage failed or underperforming jobs to resolution.
• Drive work forward independently by navigating ambiguity and technical roadblocks, delivering incremental improvements that get capabilities into users' hands quickly.
• Enjoy working in a fast-paced, design-driven product development environment, balancing stability with rapid iteration and experimentation.
• Embody ourCultureandValues.

• Do you have a Bachelor's degree in computer science, or related technical field AND 4+ years technical engineering experience with deploying or operating on-premise or cloud high-performance clusters, AND 4+ years experience working with high-scale training clusters (ex. working with frameworks/tools such as nvidia InfiniBand clusters, SLURM, Kubernetes, Ray, etc.), AND 4+ years experience building scalable services on top of public cloud infrastructure like Azure, AWS, or GCP,

• OR equivalent experience?, * Master's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with deploying or operating on-premise or cloud high-performance clusters, AND 6+ years experience working with high-scale training clusters (ex. working with frameworks/tools such as nvidia InfiniBand clusters, SLURM, Kubernetes, Ray, etc.), AND 6+ years experience building scalable services on top of public cloud infrastructure like Azure, AWS, or GCP,
• OR equivalent experience.

• Experience with LLM training clusters
• Experience working with AI platforms, frameworks, and APIs
• Experience using Machine Learning frameworks, including experience using, deploying, and scaling language learning models, either personally or professionally.
• Experience working with large-scale HPC or GPU systems (ex. NVIDIA H100/GB200 or equivalent).
• Ability to identify, analyze, and resolve complex technical issues, ensuring optimal performance, scalability, and user experience.
• Dedication to writing clean, maintainable, and well-documented code with a focus on application quality, performance, and security.
• Demonstrated interpersonal skills and ability to work closely with cross-functional teams, including product managers, designers, and other engineers.
• Ability to clearly communicate complex technical concepts to both technical and non-technical stakeholders.
• Passion for learning new technologies and staying up to date with industry trends, best practices, and emerging technologies.
• Ability to work in a fast-paced environment, manage multiple priorities, and adapt to changing requirements and deadlines.
• Proven ability to collaborate and contribute to a positive, inclusive work environment, fostering knowledge sharing and growth within the team.

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