LLMOps/MLOps Engineer (Immediate Joiners/Currently Serving) (Telangana)

We are looking for IMMEDIATE JOINERS or Serving Notice period candidates only, interested and eligible candidates can apply with their updated resume. Experience 5+ Years Location Pune, Hyerabad Detailed JD MLOps/LLMOps Engineer with a solid background in continual learning, cloud infrastructure, Azure, GCP, and AWS. The ideal candidate will have extensive hands-on experience in Python and ML libraries (Scikit-learn, TensorFlow, PyTorch), and a proven track record in deploying, monitoring, and optimizing machine learning and large language model pipelines. Core Responsibilities & Skills: 1. MLOps & LLMOps Pipeline Development - Design, implement, and automate end-to-end ML/LLM pipelines with a focus on continual learning, model retraining, and A/B testing. - 2. Cloud & Infrastructure Expertise - Strong hands-on experience with Azure, GCP, and AWS cloud platforms, including managed services for ML (Azure ML, Sagemaker, Vertex AI). - Proficiency in Docker, Kubernetes, and cloud-native architectures for scalable, containerized deployments. 3. ML & LLM Tools & Frameworks - Expertise in ML pipeline tools: MLflow, Airflow, Kubeflow, Sagemaker, Azure ML. - Experience with LLM tools and frameworks: LangChain, LlamaIndex, Hugging Face, OpenAI/Azure OpenAI APIs. - Hands-on experience with vector databases: Pinecone, Weaviate, Chroma, Qdrant. 4. Monitoring, Optimization & Scalability - Implement monitoring and observability using tools like Prometheus, Grafana, ELK, and Datadog. - Optimize GPU compute, inference latency, and model serving for high-performance, scalable architectures. 5. Programming & Collaboration - Strong Python skills and familiarity with ML libraries (Scikit-learn, TensorFlow, PyTorch). - Collaborate with data scientists, engineers, and product teams to deliver robust, production-grade ML/LLM solutions. .