We are hiring: MLOps Engineer Coforge Ltd.

Job description

**We are hiring: MLOps Engineer Coforge Ltd.** We are inviting applications for an experienced MLOps Engineer with strong expertise in continual learning, CI/CD pipelines, and cloud infrastructure. The ideal candidate should have hands-on experience in deploying, monitoring, and optimizing Machine Learning and Large Language Model (LLM) pipelines across cloud platforms. **Join This WhatsApp Group for Regular and Quick Job Updates.** **Click On the Link:-** **https://chat.whatsapp.com/LW8Dnu6IZ54HzkZVMakCE7** - **Email:** **Gaurav.2.Kumar@coforge.com** - **WhatsApp:** 9667427662 **Interview Details:-** - **Interview Dates:** 13th June 2026 - Saturday - **Mode:** Microsoft Teams (Video Call) - **Time:** 10:00 AM to 5:00 PM - **Duration:** 45 Minutes **Job Details:-** - **Experience Required:** 5 to 10 Years - **Employment Type:** Full-Time - **Work Location:** Greater Noida, Pune, and Hyderabad Only **Job Description:-** **1. MLOps & LLMOps Pipeline Development:-** - Design and implement end-to-end ML/LLM pipelines with focus on continual learning, retraining, and A/B testing - Integrate CI/CD pipelines for model deployment, versioning, and rollback **2. Cloud & Infrastructure Expertise:-** - Strong hands-on experience with Azure, AWS, and GCP (Azure ML, SageMaker, Vertex AI) - Expertise in Docker, Kubernetes, and scalable cloud-native architectures **3. ML & LLM Tools & Frameworks:-** - Experience with ML tools: MLflow, Airflow, Kubeflow, SageMaker, Azure ML - Knowledge of LLM 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 using Prometheus, Grafana, ELK, Datadog - Optimize GPU utilization, inference latency, and model performance **5. Programming & Collaboration:-** - Strong Python skills with knowledge of Scikit-learn, TensorFlow, PyTorch - Collaborate with cross-functional teams to deliver production-grade ML/LLM solutions