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.

📌 LLMOps/MLOps Engineer (Immediate Joiners/Currently Serving) (Telangana)
🏢 Coforge
📍 Telangana