AI/HPC System Performance Engineer
Tasks
- Analyze RDMA fabrics and collective communication libraries issues
- Build monitoring tooling to detect anomalies and reduce mean time to mitigation
- Design and execute capacity and scalability experiments
- Develop performance analysis frameworks and dashboards
- Establish service level objectives for network performance and reliability
- Identify network compute and memory bottlenecks
- Investigate and resolve performance regressions in distributed AI training
- Lead technical design reviews for network and system changes
- Mentor engineers on HPC performance debugging and instrumentation
- Profile and benchmark AI training and inference workloads
- Support distributed job scheduling performance investigations
- Track GPU utilization network bandwidth latency and collective communication metrics
Perks/Benefits
- N/A
Skills/Tech-stack
Alerting | Anomaly Detection | Artificial Intelligence | C# | C++ | Capacity Planning | Collective communication | Distributed Computing | GPU Utilization | GPU interconnects | HPC | Infiniband | Instrumentation | Job Scheduling | Latency | MPI | Machine Learning | NCCL | Network bandwidth | Operating System | Performance Monitoring | PyTorch | Python | RDMA | RoCE | Scalability testing | Telemetry | TensorFlow
Education
N/A
Regions
Countries
States
Cities
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