We are seeking an experienced AI/ML Ops Engineer to bridge the gap between data science and DevOps. The ideal candidate will operationalize machine learning models, automate workflows, and maintain scalable infrastructure for AI applications.

Key Responsibilities :

- Implement CI/CD pipelines for ML models using GitHub and DevOps best practices.

- Deploy and monitor models using AI frameworks such as PyTorch and TensorFlow.

- Integrate LangChain, LangFuse, and Vector Databases for LLM-based applications.

- Build and optimize APIs and microservices using FastAPI.

- Manage deployments on Kubernetes clusters, ensuring scalability and reliability.

- Collaborate with data scientists and engineers to enhance model lifecycle management.

Required Skills :

- Proficiency in Python, FastAPI, and ML frameworks (PyTorch, TensorFlow).

- Strong knowledge of DevOps tools, GitHub Actions, and Kubernetes.

- Experience with LangChain, LangFuse, and Vector Databases.

- Hands-on with Terraform, CI/CD automation, and container orchestration.