Data Scientist

Job Description

We are looking for an experienced Data Scientist with strong expertise in Statistical Machine Learning, Generative AI/LLMs, and Computer Vision. The ideal candidate will design and deploy end-to-end AI and machine learning solutions across structured data, text, and image modalities while driving innovation through advanced analytics and modern AI technologies. The candidate should have hands-on experience building production-grade machine learning models, fine-tuning large language models, implementing RAG pipelines, and developing computer vision solutions. Key Responsibilities Design, develop, and deploy end-to-end machine learning solutions. Build and fine-tune Large Language Models for domain-specific applications. Develop Retrieval-Augmented Generation (RAG) pipelines and AI assistants. Implement computer vision solutions for detection, segmentation, and classification tasks. Conduct statistical analysis, A/B testing, causal inference, and experimentation. Evaluate and integrate foundation models and open-source AI models. Monitor model performance, drift, retraining, and version control. Collaborate with cross-functional teams to deliver AI-driven business solutions. Mentor junior data scientists and contribute to AI best practices. Optimize inference costs, context windows, and model performance. Develop internal tools, evaluation frameworks, and deployment pipelines. Mandatory Skills Statistical Machine Learning Probability Theory and Statistics Bayesian Inference Hypothesis Testing Causal Inference Survival Analysis Ensemble Learning XGBoost LightGBM Support Vector Machines (SVM) Regularized Regression PyMC, Stan, or Pyro LLMs & Generative AI Llama, Mistral, Falcon RAG Pipelines LangChain Vector Databases (Pinecone, Chroma, Weaviate, FAISS) Prompt Engineering LoRA and QLoRA Fine-Tuning Embeddings and Vector Search LLM Evaluation (RAGAS, LangSmith) Agentic AI Workflows Computer Vision YOLO Detectron2 Segment Anything Model (SAM) Vision Transformers (ViT) CLIP DINO Image Classification Object Detection Image Segmentation Multimodal Models (LLaVA, GPT-4V, Gemini) Required Qualifications Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, or related field. 7–8 years of experience in Data Science and Machine Learning. Strong Python programming skills. Experience with production ML systems and MLOps practices. Preferred Skills MLOps and model deployment experience. Cloud platforms such as AWS, Azure, or GCP. Docker and Kubernetes. Experiment tracking and model monitoring tools. Leadership and mentoring experience. Soft Skills Excellent analytical and problem-solving skills. Strong communication and stakeholder management. Team collaboration and leadership abilities. Ability to work independently in a remote environment. Strong organizational and project management skills.