AI Infrastructure Engineer

5 - 9 years

0 Lacs

Posted:3 weeks ago| Platform: Shine logo

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On-site

Job Type

Full Time

Job Description

As an AI Infrastructure Engineer (DevOps/MLOps) at Techvantage.ai, you will be responsible for building and managing the cloud infrastructure, deployment pipelines, and machine learning operations supporting our AI-powered products. Your role will involve collaborating at the intersection of software engineering, ML, and cloud architecture to ensure scalability, reliability, and production-readiness of our models and systems. **Key Responsibilities:** - Design and manage CI/CD pipelines for software applications and machine learning workflows. - Deploy and monitor ML models in production using tools like MLflow, SageMaker, Vertex AI, or similar. - Automate infrastructure provisioning and configuration with IaC tools (Terraform, Pulumi, etc.). - Establish monitoring, logging, and alerting systems for AI applications. - Manage containerized services with Docker and Kubernetes. - Collaborate with data scientists and ML engineers for model experimentation, versioning, and deployment. - Optimize compute resources and storage costs across AWS, GCP, or Azure. - Ensure system reliability, scalability, and security in all environments. **Qualifications Required:** - 5+ years experience in DevOps, MLOps, or infrastructure engineering. - Hands-on experience with cloud platforms (AWS, GCP, or Azure) for ML workloads. - Proficiency in CI/CD tools (e.g., GitHub Actions, Jenkins, GitLab CI). - Strong knowledge of Docker, Kubernetes, and infrastructure-as-code frameworks. - Experience with ML pipelines, model versioning, and monitoring tools. - Scripting skills in Python, Bash, or similar for automation. - Familiarity with monitoring/logging tools like Prometheus, Grafana, ELK, CloudWatch. - Understanding of ML lifecycle management and reproducibility. At Techvantage.ai, you will have the opportunity to work on cutting-edge AI platforms and infrastructure, engage in cross-functional collaboration with top ML, research, and product teams, and receive a competitive compensation package without constraints for the right candidate.,

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