MLOps Engineer

Tasks

• Build and maintain inference pipelines
• Build and maintain training pipelines
• Build scalable runtime infrastructure
• Contribute to platform capabilities
• Establish CI/CD patterns
• Integrate monitoring and alerting
• Optimize compute workloads
• Set up and manage ML environments
• Troubleshoot networking and training errors

Perks/Benefits

• N/A

Skills/Tech-stack

C++ | Containerization | Deep learning | Distributed Training | Docker | High Performance | High-Performance Computing | Inference Serving | Kubernetes | ML platform | ML platform management | MPI | Model Pipelines | NCCL | Network Troubleshooting | Performance Computing | Platform management | PyTorch | Python