Lead AI/ML Engineer

Recro; Bengaluru; On-site; INR 400,000 - 900,000; Full time

Job summary

Recro is seeking a Lead AI/ML Engineer in Bengaluru to build, fine-tune, and deploy domain-specific LLMs and GenAI solutions for telecom applications.

You will implement prompt engineering frameworks, RAG pipelines, and multi-agent workflows while collaborating with data engineering, product, and telecom teams to deliver production-ready AI systems.

Qualifications

• 8+ years in AI/ML, incl. 2+ years in LLM/GenAI deployments.
• Master’s or Ph.D. in Computer Science, AI/ML, NLP, or related field; Ph.D. preferred.

Responsibilities

• Build and fine-tune LLMs such as GPT, Llama, and Mistral.
• Develop prompt engineering frameworks and RAG pipelines.
• Implement vector databases like FAISS and Pinecone.
• Build multi-agent workflows using LangChain, LlamaIndex, and LangGraph.
• Evaluate models to reduce hallucinations and improve accuracy.
• Deploy production-ready AI solutions in collaboration with data engineering and telecom teams.

Skills

Python

PyTorch

NLP

Transformer architectures

Model evaluation

Education

Master's degree in CS/AI/ML

PhD preferred

Tools

Hugging Face Transformers

FAISS

Pinecone

LangChain

LlamaIndex

Job description

Experience: 8+ years in AI/ML, including 2+ years in LLM/GenAI deployments

Education: Master’s or Ph.D. in Computer Science, AI/ML, NLP, or a related field; Ph.D. preferred.

Role Overview

We are looking for a Lead AI/ML Engineer to build, fine-tune, and deploy domain-specific LLMs and GenAI solutions for telecom business applications.

Key Responsibilities

• Build and fine-tune LLMs such as GPT, Llama, and Mistral.
• Develop prompt engineering frameworks and RAG pipelines.
• Implement vector databases such as FAISS and Pinecone.
• Build multi-agent workflows using LangChain, LlamaIndex, and LangGraph.
• Evaluate models to reduce hallucinations and improve accuracy.
• Deploy production-ready AI solutions and collaborate with data engineering, product, and telecom domain teams.

Required Technical Skills

• Strong Python, PyTorch, Hugging Face Transformers, and NLP.
• LLM fine-tuning techniques: LoRA, PEFT, adapters, and transfer learning.
• Prompt engineering, RAG architecture, and LLM orchestration.
• Transformer architectures, model deployment, and production AI solutions.

Good to Have

• Telecom domain experience with call records, customer tickets, or network logs.
• Multimodal LLMs, OpenAI function calling, and agent-based orchestration.
• Low-latency inference optimization, quantization, and distillation.