DataOps Engineer (AI Platform Engineer)
Tasks
- Build and maintain CI CD pipelines for model delivery
- Build and maintain model lifecycle tooling
- Build and maintain observability for GPU clusters
- Build and operate on prem AI platform
- Configure GPU MIG based on workloads
- Deploy and scale model inference
- Design deploy and maintain model serving runtimes
- Enable model fine tuning workflows
- Ensure platform security compliance
- Evaluate and benchmark inference performance
- Integrate tracing for inference workflows
- Manage GPU operations in Kubernetes
- Manage model inputs and configurations
- Run performance testing for multi node GPU clusters
Perks/Benefits
- Company car
- Education allowance
- Employee share scheme
- Gym access
- Health insurance
- Paid time off
- Relocation support
- Relocation visas and legal assistance
- Unlimited learning opportunities
Skills/Tech-stack
AMD ROCm | CI/CD | Distributed Systems | GPU MIG | Go | High Performance | High-performance networking | KServe | Kubernetes | Linux | LoRA | Logging | MLflow | Metrics | Model Serving | NVIDIA CUDA | NVIDIA Triton | ONNX | Python | RDMA | SGLang | Tracing | VLLM
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Platform Engineer | DataOps Engineer | Engineer | Platform Engineer
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