Data Scientist

Role & responsibilities:

• Develop and deploy machine learning and Generative AI models including LLM-based solutions, RAG architectures, and prompt-driven workflows.
• Work on model fine-tuning, embeddings, vector search, and retrieval optimization.
• Conduct exploratory data analysis and apply suitable ML techniques to solve business problems.
• Build and maintain model training pipelines and automate model evaluation and monitoring.
• Deploy ML/AI solutions on AWS services such as SageMaker, Lambda, S3, and API Gateway.
• Collaborate with cross-functional teams to define problem statements and deliver AI-driven insights.
• Ensure best practices in model governance, documentation, versioning, and performance tuning.
• Continuously research and experiment with new GenAI models, frameworks, and techniques.

Required Skills & Qualifications:

•4+ years of experience in Data Science / Machine Learning.

•Strong experience in Generative AI, LLMs, RAG pipelines, tokenization, and embeddings.

•Good understanding of ML algorithms, deep learning concepts, and model evaluation techniques.

•Experience working with AWS cloud (SageMaker, EC2, S3, Lambda, etc.).

• Working knowledge of Python for model building (basic to intermediate).

• Basic exposure to SQL or other query languages for data extraction (not mandatory).

• Strong analytical thinking and ability to work with large datasets.

• Good communication and presentation skills.

Preferred Qualifications:

• Experience using vector databases (Pinecone, FAISS, Weaviate).

• Familiarity with MLOps practices and tools for automation.

• Exposure to API integration and production deployment of GenAI/ML models.

• AWS or AI/ML-related certifications.