AI/ML Engineer

Job Summary We are looking for a skilled

AI/ML Engineer

to design, build, and deploy scalable machine learning solutions with a strong focus on

Large Language Models (LLMs) . The role involves working on data ingestion, vector databases, model integration, and optimization of AI-driven applications such as

RAG systems, semantic search, and intelligent automation .

Roles & Responsibilities

Design, develop, and deploy

AI/ML solutions

using classical ML and

LLM-based architectures . Build and maintain

end-to-end data pipelines

including data scraping, preprocessing, chunking, embedding generation, and storage. Implement and optimize

vector databases

(e.g., VectorDB, Pinecone, FAISS, Weaviate) for semantic search and retrieval. Develop

RAG (Retrieval-Augmented Generation)

pipelines integrating LLMs with structured and unstructured data sources. Monitor model performance, latency, and retrieval accuracy; fine-tune models and embeddings as required. Collaborate with product, data, and engineering teams to translate business requirements into AI solutions. Ensure best practices in

model versioning, experimentation, and MLOps .

Required Skills & Qualifications

Strong proficiency in

Python

and ML frameworks (PyTorch, TensorFlow, scikit-learn). Should have

3+ years

of experience in similar role. Hands-on experience with

LLMs

(OpenAI, Hugging Face, LLaMA, Mistral, etc.). Experience working with

vector databases

and embedding models. Solid understanding of

NLP, transformers, embeddings, and similarity search algorithms . Experience building

production-grade ML systems

and APIs (FastAPI, Flask). Familiarity with

cloud platforms

(AWS, GCP, Azure) and containerization (Docker, Kubernetes).