Data Scientist

As a Data Scientist with 4+ years of experience, your role will involve designing, developing, and deploying end-to-end ML and NLP solutions. You will be responsible for building RAG-based pipelines using vector stores and LLMs for real-world use cases, developing embedding pipelines using OpenAI, HuggingFace, SentenceTransformers, and more. Additionally, you will perform data cleaning, transformation, feature engineering, EDA, fine-tune foundational models, and apply few shot / in-context prompting techniques. Collaboration with Engineering and Product teams to translate business problems into AI solutions and contributing to MLOps workflows including model deployment, testing, and CI/CD will also be part of your responsibilities. Lastly, preparing analytics dashboards, visualizations, and insights for stakeholders will be crucial. Key Responsibilities: - Design, develop, and deploy end-to-end ML and NLP solutions. - Build RAG-based pipelines using vector stores and LLMs for real-world use cases. - Develop embedding pipelines using OpenAI, HuggingFace, SentenceTransformers, etc. - Perform data cleaning, transformation, feature engineering, and EDA. - Fine-tune foundational models and apply few shot / in-context prompting techniques. - Build reusable components leveraging LangChain, LlamaIndex, and other LLM toolkits. - Collaborate with Engineering and Product teams to convert business problems into AI solutions. - Contribute to MLOps workflows including model deployment, testing, and CI/CD. - Prepare analytics dashboards, visualizations, and insights for stakeholders. Qualifications Required: - Bachelor's or Master's degree in Computer Science, Data Science, AI, or related field. - 4+ years hands-on experience in Machine Learning / NLP / GenAI. - Practical experience with RAG architectures & vector databases (FAISS / Pinecone / Weaviate / ChromaDB). - Proficiency in Python, LangChain, LlamaIndex, and LLM frameworks (OpenAI, HuggingFace Transformers). - Strong experience in Pandas, NumPy, Matplotlib for data manipulation & visualization. - Experience in LLM fine-tuning, prompt engineering, and in-context learning strategies. - Cloud AI platform experience (AWS Sagemaker / Azure AI / Google Vertex AI). - Experience integrating models into APIs and production systems (MLOps, CI/CD). - Strong analytical mindset with the ability to communicate insights to both tech and business stakeholders. - Hands-on experience with RAG architectures, vector databases (FAISS, Pinecone, Weaviate, ChromaDB), and embedding generation (OpenAI, SentenceTransformers, HuggingFace). Nice to Have: - Experience with Kafka, Spark, or real-time data processing frameworks. - Exposure to vector search optimization and prompt evaluation metrics. - Knowledge of multi-agent AI frameworks / orchestration engines. Please note that this is a full-time, permanent position based in Pune.,