Valuedx Technologies - Data Scientist

Description: Engineer LLM (AI & Data Science Expert)

Experience: 5+ Years (3+ Years in AI & Data Science)

Location: Pune / Remote

About the Role:

We are seeking a AI Engineer expert to drive AI strategy, architecture, and development.

This role requires expertise in LLMs, RAG, multi-agent AI frameworks, vector databases, and AI security.

You will lead a team in building scalable AI applications, with a focus on LLM-driven solutions, AI-powered automation, and Conversational AI chatbots.

Key Responsibilities:

Leadership & AI Solutioning:

- Define AI system architectures integrating LLMs, multi-agent AI, and secure AI solutions.

- Collaborate with product teams and stakeholders to design AI-driven applications.

- Research and implement cutting-edge AI innovations in retrieval-augmented generation (RAG) and LLM fine-tuning.

AI & Machine Learning Development:

- Expertise in LLMs, Advanced RAG techniques, and knowledge retrieval using vector databases (FAISS, Quadrant, Chroma).

- Hands-on experience with multi-agent AI frameworks like AutoGen for intelligent automation.

- Develop and optimize AI workflows using LangChain, LlamaIndex, and LangGraph for real-time AI-driven applications.

- Implement LLM security frameworks (Guardrails, LLM Guard, AI Red Teaming) to ensure ethical AI usage.

- Develop Conversational AI chatbots for enterprise applications using LLMs and NLP frameworks.

- Experience in deep learning using TensorFlow, PyTorch, and fine-tuning open-source LLMs.

API & Backend Engineering:

- Develop and optimize RESTful APIs using FastAPI.

- Work with relational & NoSQL databases for AI-driven applications.

- Design and implement scalable microservices architectures for AI model deployment.

- Integrate and deploy LLMs for real-time AI-powered solutions with optimized response times.

Cloud & DevOps (Good to Have):

- Experience with AWS, Azure for scalable AI deployments.

- Familiarity with Docker & Kubernetes for containerized AI solutions.

- Exposure to CI/CD pipelines for automated AI model deployment.