AI/ML Platform Engineer (Kubernetes & MLOps)

We are seeking an MLOps/AI Platform Engineer to build, deploy, and scale production AI/ML services on Kubernetes. You will partner with ML engineers and software teams to operationalize models with strong reliability, performance, and cost efficiency using automated pipelines, monitoring, and end-to-end MLOps practices.

Own the deployment and operational excellence of AI/ML services by establishing robust CI/CD, model serving, observability, and lifecycle management on Kubernetes—optimizing inference performance (latency/throughput), ensuring reliable releases, and reducing infrastructure and operating costs.

• Kubernetes
• Docker
• CI/CD (GitHub Actions/Jenkins)
• Python
• REST/gRPC model serving
• MLflow
• TensorFlow or PyTorch
• Prometheus/Grafana
• Kafka/RabbitMQ
• Monitoring and alerting
• Automated MLOps practices
• Model performance optimization
• Cost optimization

• Kubernetes
• Docker
• Python
• MLflow
• TensorFlow or PyTorch
• REST/gRPC model serving
• CI/CD (GitHub Actions/Jenkins)
• Prometheus/Grafana
• Kafka/RabbitMQ
• AWS/GCP/Azure basics
• Monitoring and incident response
• MLOps/production AI experience