lever
MLOps / AI Infrastructure Engineer
jobgether
Remote, IND
Full-time
Remote
INR 1,800,000–2,500,000.
Discovered 2 weeks ago
PythonDockerKubernetesTerraformCloud platformsModel deployment
Free
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Role Overview
Build and operate the systems that power production-scale machine learning and generative AI workloads.
Work across software engineering, data science, cloud infrastructure, and AI research to turn experimental models into reliable production services.
Key Skills for This Role
PythonDockerKubernetesTerraformCloud platformsModel deployment
Full Job Posting
Role Overview
Build and operate the systems that power production-scale machine learning and generative AI workloads.
Work across software engineering, data science, cloud infrastructure, and AI research to turn experimental models into reliable production services.
Accountabilities
- Architect and maintain model deployment and serving pipelines for LLMs, deep learning models, and predictive analytics workloads.
- Develop model-serving architectures using Triton, Ray, BentoML, or comparable platforms.
- Automate CI/CD across data ingestion, feature management, training, validation, deployment, and monitoring.
- Manage Kubernetes and other containerized workloads across cloud environments.
- Monitor GPU and CPU clusters and optimize performance, availability, resource efficiency, and cloud expenditure.
- Collaborate with data scientists and AI researchers to productionize resilient, scalable, low-latency services.
- Improve infrastructure automation, observability, reliability, and the ML platform continuously.
Requirements
- Have 4–8 years of relevant professional experience with significant exposure to ML systems.
- Have strong Python proficiency and hands-on experience with Docker, Kubernetes, and Terraform.
- Have practical experience with cloud platforms and managed AI/ML services such as AWS Bedrock, Amazon SageMaker, Google Cloud Vertex AI, or equivalents.
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