Job Description & Summary: A career within…. A career within Data and Analytics services will provide you with the opportunity to help organizations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organizational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organizations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge.  

 Responsibilities: 

 Design RAG/LLM pipelines for experiment management, model management, feature management, and model retraining. 

• Design APIs for model inferencing at scale. 

• Proven expertise with MLflow, SageMaker, Vertex AI, and Azure AI. 

• LLM Serving & GPU Architecture: Deep knowledge of GPU architectures, distributed training, and serving of large language models. 

• Model Fine-Tuning & Optimization: Improve latencies, accuracies, and reduce resource requirements for fine-tuning LLM/LVM models. 

•  DevOps & LLMOps Proficiency: Expertise in Kubernetes, Docker, Container Orchestration, and LLM orchestration frameworks (Flowise, Langflow, Langgraph). 

Mandatory skill sets: 

• Gen AI, LLM, Hugging Face 

• Python, PyTorch/TensorFlow/Keras 

•  Langchain, Langgraph 

• Docker, Kubernetes 

Preferred skill sets: 

•  Databases/Datawarehouse: DynamoDB, Cosmos, MongoDB, RDS, MySQL, PostgreSQL, Aurora, Spanner, BigQuery 

• Cloud Knowledge: AWS, Azure, GCP 

• DevOps Tools: FluentD, Kibana, Grafana, Prometheus 

• Proficient in Python, SQL, JavaScript 

Years of experience required: 

11-15 

Education Qualification

B.Tech / M.Tech / MBA / MCA