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Principal Solutions Engineer, Infrastructure (SLURM & AI Focus)

THE ROLE:

The AMD Datacenter GPU team is seeking an experienced Solutions Engineer specializing in high-performance computing infrastructure for AI workloads. This role focuses on designing, deploying, and optimizing GPU-accelerated computing environments for AI use-cases using SLURM as the primary workload manager.

THE PERSON:

The ideal candidate will have deep expertise in Multi-tenant Schedulers for large scale AI Clusters, RDMA networking, collective communications, container orchestration, and storage solutions optimized for AI/ML workloads.

KEY RESPONSIBILITIES:

AI Infrastructure Design

• Build and design large GPU-accelerated clusters for AI/ML workloads
• Develop reference architectures for SLURM-based HPC environments
• Integrate SLURM with Kubernetes for hybrid workload management
• Design storage systems to support high-speed AI training pipelines

SLURM Optimization & Management

• Configure and optimize SLURM for efficient AI/ML scheduling and resource use
• Use advanced SLURM features such as GPU-aware scheduling, MPI integration, container runtime support, and fair-share policies
• Develop SLURM plugins and customizations for AI workloads

Networking & Interconnect

• Design RDMA network setups (InfiniBand, RoCE) for fast data transfer
• Optimize collective communications for distributed training (e.g., All Reduce)
• Configure GPU Direct RDMA and topology-aware job scheduling

Storage Solutions

• Architect parallel file systems like Lustre, GPFS, BeeGFS for AI data needs
• Implement high-performance scratch storage and tiered data management
• Optimize I/O patterns and manage data lifecycle for training datasets

Container Orchestration & Integration

• Collaborate on Kubernetes operators for SLURM integration
• Develop strategies for seamless containerized AI workload management
• Build CI/CD pipelines and enable hybrid cloud deployments

Collaboration & Support

• Work with research teams and customers to meet AI computing needs
• Provide technical guidance and training
• Create documentation and best practices
• Partner with vendors on hardware and software selection

PREFERRED EXPERIENCE:

Technical Skills

• Extensive SLURM experience in production HPC environments
• Expert knowledge of RDMA technologies and collective communications
• Hands-on GPU computing and Linux system administration skills
• Experience with parallel file systems and scripting (Python, Bash, Go)

Container & Orchestration

• Production Kubernetes experience in HPC settings
• Familiarity with Kubernetes SLURM plugin and container runtimes (Singularity, Docker)
• Experience with Helm and Kubernetes operators

AI/ML Infrastructure

• Understanding AI frameworks (PyTorch, TensorFlow, JAX) and distributed training
• Knowledge of AI workload optimization and MLOps practices

EDUCATION:

• Bachelor’s degree in Computer Science, Engineering, or related field
• Advanced degree preferred

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Benefits offered are described: AMD benefits at a glance.

AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.