Senior Data Scientist

Role Overview

As a Senior Data Scientist specializing in AI, you will be a key individual contributor responsible for the research, design, and implementation of advanced generative AI models. You will tackle some of our most complex business challenges, transforming concepts into tangible, high-impact AI solutions. This role requires a deep technical background in machine learning, deep learning, statistical modelling, and generative AI techniques, including LLMs, diffusion models, and agentic systems. You will own projects end-to-end, from ideation to production, building models that push the boundaries of what's possible.

Key Responsibilities

• Design, develop, and deploy generative AI models, including LLMs and diffusion models.
• Implement Retrieval-Augmented Generation (RAG) pipelines with standard, graph-based, and vector DB integrations (FAISS, Pinecone, Weaviate, Milvus).
• Orchestrate multi-agent AI systems using frameworks like LangGraph, AutoGen, Semantic Kernel, and OpenAI tool-calling APIs.
• Fine-tune LLMs (Llama3, Mistral, CodeLlama, Falcon) and diffusion models (Stable Diffusion, Flux.1, ControlNet, DreamBooth) using parameter-efficient methods such as LoRA, QLoRA, and adapters.
• Conduct advanced prompt engineering, including system prompting, function calling, and safety alignment.
• Apply classical ML and deep learning techniques for structured and unstructured data, including CNNs, RNNs/LSTMs, Transformers, and Graph Neural Networks.
• Develop solutions for computer vision tasks, including object detection (YOLO, DETR, Faster R-CNN, SSD), OCR (PaddleOCR, Tesseract, LayoutLM), video analytics, and multi-modal ML (CLIP, BLIP, SAM).
• Optimize and deploy models using TensorRT, ONNX Runtime, quantization, pruning, and distillation.
• Build scalable AI services using Docker, Kubernetes, REST/gRPC APIs, and Azure AI/ML cloud services.
• Monitor deployed models for performance and drift using tools like Prometheus, Grafana, ELK stack, and Azure Monitor.

Required Technical Expertise

Languages & Frameworks

• Python (advanced data structures, async, multiprocessing)
• Deep learning frameworks: PyTorch, TensorFlow, JAX
• HuggingFace Transformers & Diffusers
• LLM/agentic frameworks: LangChain, LangGraph, LlamaIndex, Semantic Kernel
• MLOps: MLflow, Weights & Biases, Kubeflow
• Graph RAG, MCP frameworks
• CUDA libraries & GPU optimization (CuGraph, CuPy)

Machine Learning & Deep Learning

• Classical ML: XGBoost, LightGBM, CatBoost, linear/logistic regression, clustering, dimensionality reduction
• Deep learning: CNNs, RNNs, LSTMs, GRUs, Transformers (BERT, ViT, GPT)
• Graph ML: Graph Neural Networks (GraphSAGE, GAT, PyTorch Geometric, DGL)
• Time series forecasting: Prophet, ARIMA, DeepAR, Temporal Fusion Transformer
• Reinforcement Learning: RLHF, PPO, DQN, policy gradients

Computer Vision & Multi-modal AI

• Object detection, OCR, video analytics, multi-modal ML (vision-language)

Optimization & Deployment

• Model optimization: TensorRT, ONNX Runtime, quantization, pruning, distillation
• Scalable deployment: Docker, Kubernetes, REST/gRPC APIs, Azure Functions
• Cloud: Azure AI/ML services (App Service, Azure OpenAI, AML)
• Monitoring: Azure Monitor, Prometheus, Grafana, ELK stack

Qualifications

• Master’s or Bachelor’s degree in Computer Science or related field
• 3.5–7 years of AI/ML experience with end-to-end solution delivery
• Hands-on experience productionizing ML/LLM solutions (PoC → scalable deployment → monitoring & maintenance)
• Strong foundation in ML/DL theory (optimization, loss functions, architectures)
• Applied research/engineering experience (publications, open-source contributions, or patents) is a plus
• Excellent analytical, problem-solving, and debugging skills

Job Type: Full-time

Pay: ₹90,000.00 - ₹100,000.00 per month

Work Location: In person