AI / ML Engineer

VectovateAI Software Solutions Pvt. Ltd.; India; On-site; INR 1,800,000 - 2,600,000; Full time

Job summary

VectovateAI Software Solutions Pvt. Ltd. is seeking an elite AI/ML Engineer to build production-grade AI systems for enterprise clients. You will bridge foundational ML with Generative AI, architect high-accuracy RAG pipelines, and deploy low-latency AI microservices.

You will lead end-to-end ML pipelines, fine-tune open-source models, implement advanced vector infrastructure, and optimize deployment for scale and reliability in production environments.

Qualifications

• 4 years of total IT/software experience, with at least 3 years deeply focused on AI, ML, and production deployments.
• Advanced proficiency in Python (asyncio, FastAPI, Pydantic) and core ML libraries (PyTorch, Hugging Face).
• Deep mastery of vector math, embedding models, tokenization, and prompt engineering.

Responsibilities

• Design and deploy advanced RAG pipelines with custom chunking strategies and hybrid search.
• Build multi-agent workflows and orchestration layers using LangChain, LlamaIndex, or custom Python loops.
• Fine-tune open-source foundation models (e.g., Llama 3, Mistral) with LoRA/QLoRA and train NLP/classification models.
• Scale vector database solutions (Pinecone, Qdrant, Milvus, pgvector) and implement automated evaluation (Ragas, TruLens).

Skills

Python

PyTorch

Hugging Face

LangChain

LlamaIndex

FastAPI

Pydantic

Docker

GPU inference

Vector math

Tools

Pinecone

Qdrant

Milvus

pgvector

TruLens

Job description

We are seeking an elite AI/ML Engineer to build production-grade artificial intelligence systems for enterprise clients. You will bridge foundational machine learning with cutting-edge Generative AI, architecting high-accuracy RAG pipelines, fine-tuning open-source models, and deploying low-latency AI microservices.

Key responsibilities

• RAG & Retrieval: Design and deploy advanced RAG pipelines featuring custom chunking strategies, hybrid search, and cross-encoder re-ranking to minimize hallucinations.
• LLM Orchestration: Build multi-agent workflows, autonomous execution loops, and orchestration layers using LangChain, LlamaIndex, or custom Python event loops.
• Machine Learning & Fine-Tuning: Apply core ML methodologies to fine-tune open-source foundation models (e.g., Llama 3, Mistral) via LoRA/QLoRA and train custom classification or NLP models.
• Vector Infrastructure & Production: Scale vector database solutions (Pinecone, Qdrant, Milvus, pgvector) and implement automated evaluation frameworks (Ragas, TruLens) for output accuracy.

What we look for

• 4 years of total IT/software experience, with at least 3 years deeply focused on AI, machine learning, and production deployments.
• Advanced proficiency in Python (asyncio, FastAPI, Pydantic) and core ML libraries (PyTorch, Hugging Face ecosystem).
• Deep mastery of vector math, embedding models, tokenization, prompt engineering, and semantic caching layers.
• Hands-on experience with Docker, cloud-based GPU instances, and high-performance inference optimization.