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:
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
Robust 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.
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.
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.
Programming & Collaboration
Robust 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.

📌 Llmops/mlops Engineer Immediate Joiners/currently Serving Telangana
🏢 Coforge
📍 Telangana