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