Description

EXPERIENCE REQUIRED
Proven track record (2+ years in applied AI/ML) of building and deploying AI solutions with measurable impact

Experience designing and managing complex AI systems such as multi-agent architectures or large-scale data pipelines

Experience with real-time communication frameworks such as LiveKit or similar technologies

Familiarity with MLOps principles and tools such as MLflow, Kubeflow, or similar platforms

Prior exposure to marketing, advertising, or consulting environments

Ability to work with ambiguous or fragmented datasets and convert them into structured, actionable outputs

Exposure to designing AI workflows and integrating APIs into AI-driven applications

KEY RESPONSIBILITIES
Design, develop, and deploy AI/ML models and intelligent applications

Build and optimize RAG-based systems using modern frameworks

Work with vector databases and manage large-scale unstructured data

Develop and integrate APIs using Python frameworks like FastAPI

Collaborate with cross-functional teams to deliver AI-driven solutions

Optimize model performance and ensure scalability of AI systems

Deploy and monitor AI solutions on cloud platforms (AWS/GCP/Azure)

Translate business requirements into technical AI implementations

KEY SKILLS & REQUIREMENTS
Hands-on experience building Retrieval-Augmented Generation (RAG) systems using frameworks such as LangChain, LangGraph, or LlamaIndex

Handson experience working with vector databases

Strong proficiency in Python, FastAPI, Celery, and core AI/ML libraries (like TensorFlow, PyTorch, scikit-learn, Hugging Face)

Solid understanding of Natural Language Processing (NLP) and working with unstructured text data

Familiarity with at least one cloud platform (AWS, GCP, or Azure) for deploying AI solutions

Good communication skills with the ability to explain technical concepts to non-technical stakeholders

Educational Qualification: B.Tech (Computer Science / IT) or MCA (preferred)

Key Skills

Education

Any Graduate