About the Role We are seeking an experienced and highly motivated Data Scientist with 4–6 years of hands-on experience in Generative AI, Machine Learning, and Deep Learning , including the development and deployment of Large Language Models (LLMs) and transformer-based architectures . You will work on cutting-edge AI solutions across various domains like NLP, Computer Vision, Reinforcement Learning , and more, contributing to both research and production-level implementations. Key Responsibilities Design, develop, and deploy machine learning models with a focus on Generative AI, NLP, and LLMs (e.g., GPT, BERT, LLaMA). Implement Retrieval-Augmented Generation (RAG) pipelines, and perform prompt engineering for various use cases. Fine-tune and optimize transformer models using frameworks like Hugging Face Transformers and LangChain . Develop and evaluate models for classification, regression, recommendation, summarization, question answering, etc. Use vector databases (e.g., Pinecone, FAISS, Weaviate, Milvus) to manage and query embeddings for scalable LLM applications. Collaborate with cross-functional teams (engineering, product, business) to deliver AI/ML solutions aligned with business goals. Utilize MLOps tools (e.g., MLflow, Kubeflow) for versioning, model monitoring, and lifecycle management. Deploy ML models to cloud platforms (preferably AWS SageMaker ) ensuring scalability and performance. Work with OpenAI, Anthropic, Cohere APIs and explore their integration into enterprise use cases. Required Skills & QualificationsCore Technical Skills Languages : Python, R, SQL Libraries/Frameworks : PyTorch, TensorFlow, Keras, Scikit-learn, XGBoost, LightGBM NLP/GenAI : Hugging Face, LangChain, LlamaIndex, RAG, Prompt Engineering LLMs : BERT, GPT, LLaMA, etc. Vector DBs : Pinecone, FAISS, Weaviate, Milvus Cloud & MLOps : AWS SageMaker, MLflow, Kubeflow Deployment : RESTful APIs, model packaging, containerization (Docker/Kubernetes a plus) Soft Skills Strong analytical and problem-solving abilities Excellent written and verbal communication skills Ability to work in a collaborative and agile team environment Nice to Have Experience with Reinforcement Learning (RL) or Computer Vision (CV) models Familiarity with Anthropic Claude, Cohere Command R+ , or similar LLMs Knowledge of data privacy, model interpretability , and AI ethics Job Type: Full-time Pay: ₹600,000.00 - ₹1,765,414.45 per year Benefits: Health insurance Provident Fund Work Location: In person
About the Role We are seeking an experienced and highly motivated Data Scientist with 4–6 years of hands-on experience in Generative AI, Machine Learning, and Deep Learning , including the development and deployment of Large Language Models (LLMs) and transformer-based architectures . You will work on cutting-edge AI solutions across various domains like NLP, Computer Vision, Reinforcement Learning , and more, contributing to both research and production-level implementations. Key Responsibilities Design, develop, and deploy machine learning models with a focus on Generative AI, NLP, and LLMs (e.g., GPT, BERT, LLaMA). Implement Retrieval-Augmented Generation (RAG) pipelines, and perform prompt engineering for various use cases. Fine-tune and optimize transformer models using frameworks like Hugging Face Transformers and LangChain . Develop and evaluate models for classification, regression, recommendation, summarization, question answering, etc. Use vector databases (e.g., Pinecone, FAISS, Weaviate, Milvus) to manage and query embeddings for scalable LLM applications. Collaborate with cross-functional teams (engineering, product, business) to deliver AI/ML solutions aligned with business goals. Utilize MLOps tools (e.g., MLflow, Kubeflow) for versioning, model monitoring, and lifecycle management. Deploy ML models to cloud platforms (preferably AWS SageMaker ) ensuring scalability and performance. Work with OpenAI, Anthropic, Cohere APIs and explore their integration into enterprise use cases. Required Skills & QualificationsCore Technical Skills Languages : Python, R, SQL Libraries/Frameworks : PyTorch, TensorFlow, Keras, Scikit-learn, XGBoost, LightGBM NLP/GenAI : Hugging Face, LangChain, LlamaIndex, RAG, Prompt Engineering LLMs : BERT, GPT, LLaMA, etc. Vector DBs : Pinecone, FAISS, Weaviate, Milvus Cloud & MLOps : AWS SageMaker, MLflow, Kubeflow Deployment : RESTful APIs, model packaging, containerization (Docker/Kubernetes a plus) Soft Skills Strong analytical and problem-solving abilities Excellent written and verbal communication skills Ability to work in a collaborative and agile team environment Nice to Have Experience with Reinforcement Learning (RL) or Computer Vision (CV) models Familiarity with Anthropic Claude, Cohere Command R+ , or similar LLMs Knowledge of data privacy, model interpretability , and AI ethics Job Type: Full-time Pay: ₹600,000.00 - ₹1,765,414.45 per year Benefits: Health insurance Provident Fund Work Location: In person