AI / ML Engineer

Build production-grade AI for enterprise clients — high-accuracy RAG pipelines, fine-tuned open-source models, and low-latency inference.

• On-site
• Full-time
• 4 Years (Min. 3 Years in AI/ML)
• Posted October 07, 2026

About the role

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.

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