Description :
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(ref : hirist.tech)