12 months ago
Bengaluru, IndiaSenior
Responsibilities
- Build and deploy LLM-powered agents for internal tools and customer-facing products.
- Design and improve RAG pipelines, prompt engineering workflows, and tool integrations.
- Experiment with open-source and closed-source LLMs.
- Implement and evaluate reasoning, planning, memory, and retrieval modules for AI agents.
- Optimize ML and LLM systems for accuracy, latency, scalability, and cost.
- Build production-ready AI/NLP pipelines with monitoring, evaluation benchmarks, and continual improvement loops.
- Collaborate with product, engineering, and customer-facing teams to ship AI features.
Requirements
- Bachelor's, master's, or doctoral degree in computer science or a mathematics-related field from a tier-1 engineering institute.
- 3+ years of industry experience in machine learning and NLP or applied AI.
- Strong programming skills in Python.
- Interest and experience with RAG and agentic AI concepts.
- Experience with PyTorch, Hugging Face Transformers, and similar ML libraries.
- Interest and experience in model training, inference optimization, and GPUs.
- Experience deploying ML services using REST APIs, Docker, Kubernetes, or cloud platforms.
- Exposure to vector databases such as FAISS, Pinecone, Qdrant, or similar.
Tech Stack
Categories
About Level AI
Level AI builds a conversational intelligence platform for enterprise contact centers, combining speech AI, NLP, and retrieval to analyze customer interactions and drive QA, coaching, automation, and analytics. It sells its software to large customer service and sales teams, typically via subscription. Founded in 2018 and headquartered in Mountain View, the company is Series C–funded, with customers such as Wayfair, Smartsheet, Chime, Gusto, and Swiss Re.