Job Summary

Architect, fine-tune, and deploy large language models (LLMs) and advanced retrieval-augmented generation (RAG) search pipelines for enterprise platforms.

As an LLM Engineer at Fospe, you will be at the forefront of designing, fine-tuning, and operationalizing cutting-edge Large Language Models and Retrieval-Augmented Generation (RAG) pipelines. You will collaborate directly with our AI research team to embed deterministic cognitive capabilities and high-throughput semantic reasoning into our vertical enterprise SaaS products.

Responsibilities
Architect, fine-tune, and quantize open-source foundation models (Llama 3, Mistral, Qwen, DeepSeek) for domain-specific enterprise workloads.
Design high-accuracy Retrieval-Augmented Generation (RAG) architectures with hybrid dense/sparse search, reranking, and semantic chunking.
Build low-latency streaming inference pipelines utilizing vLLM, TensorRT-LLM, and Triton Inference Server.
Implement guardrail validation, safety filters, prompt routing, and automated hallucination benchmarking.
Collaborate with backend engineers to expose scalable gRPC and REST interfaces for seamless frontend consumption.

Requirements
Bachelor s or Master s degree in Computer Science, Artificial Intelligence, Data Science, or related quantitative field.




3+ years of skilled experience in machine learning and deep learning, with 1+ years dedicated to LLM engineering.
Deep hands-on expertise with PyTorch, Hugging Face Transformers, vLLM, and LangChain/LlamaIndex.
Proven experience with vector databases such as Pinecone, Qdrant, Milvus, or pgvector.
Solid proficiency in Python, asynchronous programming, Docker containerization, and Linux/CUDA environments.
Demonstrated understanding of model optimization techniques including LoRA, QLoRA, AWQ, and GPTQ quantization.

Preferred Qualifications
Experience with multi-agent orchestration frameworks (LangGraph, CrewAI, AutoGen).
Contributions to open-source AI libraries or published research in NLP/LLMs.
Experience deploying models on Kubernetes and cloud infrastructure (AWS/GCP/Azure GPU instances).

Tech Stack
Python
PyTorch
Hugging Face
vLLM
LangChain
LlamaIndex
Qdrant
Docker
Kubernetes
CUDA
FastAPI

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Llm Engineer Large Language Models Bengaluru
🏢 Fospe Software
📍 Bengaluru