Data Scientist

Job Role

Location

Experience

About the Role:

We are seeking a highly skilled and experienced Senior Data Science & ML Engineer to join our innovative AI team. This role is perfect for who is passionate about building intelligent, production-ready AI systems, with a particular emphasis on Generative AI, Large Language Models (LLMs), and Agentic AI.

Key Responsibilities:

• Generative AI & LLM Systems: Design, develop, and deploy end-to-end Generative AI applications, with a strong focus on LLMs.
• Agentic AI & Orchestration: Lead the development of complex, multi-agent AI systems and sophisticated workflows using frameworks like LangChain and LangGraph.
• Retrieval Augmented Generation (RAG): Architect and implement robust RAG pipelines for enhanced LLM applications, including vector database integration and content retrieval optimization.
• Prompt Engineering Expertise: Develop and implement advanced prompt engineering strategies to optimize LLM performance, reliability, and precision for various tasks.
• LLM Fine-tuning & Customization: Perform large-scale fine-tuning and adaptation of open-source and proprietary LLMs for domain-specific applications and improved performance.
• Machine Learning Model Development: Design, train, test, and validate ML models for a wide range of tasks, including but not limited to Computer Vision (e.g., object detection, image classification, segmentation) and Natural Language Processing (e.g., text classification, sentiment analysis, entity recognition). 
• MLOps & Deployment: Build and maintain scalable and reliable production pipelines for ML models and LLM applications, ensuring seamless integration and deployment.

Required Skills & Qualifications:

• Experience: 4-5 years of hands-on experience in Data Science, Machine Learning Engineering, or a related field, with a strong portfolio of deployed solutions.
• Programming: Python
• Generative AI & LLMs: Generative AI, LLMs
• AI Orchestration: LangChain, LangGraph, Agentic AI
• LLM Techniques: RAG (Retrieval Augmented Generation), Prompt Engineering, LLM Finetuning
• ML Domains: Natural Language Processing (NLP), Computer Vision
• ML Lifecycle: End-to-end ML Model Lifecycle management
• API Development: Flask, FastAPI
• Containerization: Docker
• Rapid Prototyping: Streamlit
• Problem-Solving: Excellent analytical and problem-solving skills.

Preferred Skills (Nice-to-Haves):

• Experience with cloud platforms (AWS, Azure, GCP) and their respective AI/ML services (e.g., SageMaker, Azure ML, Vertex AI).
• Familiarity with MLOps tools and practices beyond Docker (e.g., Kubernetes, MLflow, CI/CD pipelines).
• Contributions to open-source projects or relevant publications in AI/ML conferences.
• Knowledge of vector databases (e.g., Pinecone, Weaviate, Milvus)