KEY RESPONSIBILITIES

Build the agent architecture: specialist agents for explanation, memorization, and practice behind a single companion

persona

Build the routing layer that knows the student's context and calls the right specialist at the right time

Build RAG over NCERT and curriculum content, tied to the concept hierarchy

Make the companion teach well in Hinglish tone, empathy, and code-switching that sounds like a real teacher

Own evaluation: is the explanation correct, is it pitched right, did the student actually learn — automated and human-inthe-loop

Implement mastery scoring and the logic that decides what a student sees next

Own guardrails and safety for a student-facing AI, and keep latency and cost in check at scale

REQUIRED SKILLS

5+ years in applied ML or NLP

Solid Python (PyTorch / TensorFlow / scikit-learn)

Hands-on with LLMs: prompt engineering,



RAG, embeddings, vector stores

Built multi-agent or tool-using systems in production, not just demos

Ability to design an eval suite, not just run one

Cloud ML infrastructure (GCP Vertex AI preferred; SageMaker / Azure ML also fine)

Experience taking ML systems from prototype to production

NICE TO HAVE

Education or tutoring products — knowledge tracing, mastery models, spaced repetition

Indian language NLP and Hinglish code-switching

Production experience with Gemini / Claude / GPT-class models

Speech and voice AI (Whisper, Deepgram, TTS)

Serving LLMs cheaply at scale — caching, routing, smaller models where they suffice

📌 Senior Artificial Intelligence Engineer (Uttar Pradesh)
🏢 Infinity Learn
📍 Uttar Pradesh