Senior MLOps Engineer
Tasks
- Build Kubernetes deployments for training inference
- Build internal tools for dataset curation and retraining
- Collaborate to productize LLM and speech models
- Design ML infrastructure on AWS
- Develop CI CD automation for data validation and deployment
- Ensure observability reliability and cost optimization
- Implement model serving pipelines for high throughput inference
- Integrate model demo and evaluation UIs
- Maintain Infrastructure as Code with Terraform and Helm
- Maintain model lifecycle from data ingestion to serving
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Amazon EC2 | Amazon EKS | Amazon RDS | Amazon S3 | Argo Workflows | ArgoCD | CI/CD | CloudWatch | Docker | ElevenLabs | Git | Gradio | Grafana | Helm | IAM | Kubernetes | MLflow | NCCL | OpenAI Whisper | OpenWebUI | Prometheus | Python | Ray Serve | SGLang | TensorRT | Terraform | VLLM | Weights and Biases
Education
N/A
Roles
Engineer | MLOps Engineer | Senior MLOps | Senior MLOps Engineer
Regions
Countries
States
Cities
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