AI/ML Engineer - OpenCV/Deep Learning

About The Role

We are looking for a highly skilled and forward-thinking AI/ML Engineer with 3-6 years of practical experience in building and deploying AI-powered solutions for industrial automation, computer vision, and LLM-based applications. The ideal candidate should have experience with the latest AI tools and frameworks including LangChain, LangGraph, Vision Transformers, and MLOps on AWS (SageMaker), as well as expertise in building multi-agent chat applications with React agents and vector-based RAG (Retrieval-Augmented Generation) :

• Design, train, and deploy AI/ML models for industrial automation, including computer vision systems using OpenCV and deep learning frameworks.
• Develop multi-agent chat applications integrating LLMs, React-based agents, and contextual memory.
• Implement Vision Transformers (ViTs) for advanced visual understanding tasks.
• Utilize LangChain, LangGraph, and RAG techniques to create intelligent conversational systems with vector embeddings and document retrieval.
• Fine-tune pre-trained LLMs for custom enterprise use cases.
• Collaborate with frontend teams to build responsive, intelligent UIs using React + AI backends.
• Deploy AI solutions on AWS Cloud, leveraging SageMaker, Lambda, S3, and related MLOps tools for model lifecycle management.
• Ensure high performance, reliability, and scalability of deployed AI systems.

• 3-6 years of hands-on experience in AI/ML engineering, preferably with industrial or automation-focused projects.
• Proficiency in Python and frameworks like PyTorch, TensorFlow, Scikit-learn.
• Strong understanding of LLMs (GPT, Claude, LLaMA, etc.), prompt engineering, and fine-tuning techniques.
• Experience with LangChain, LangGraph, and RAG-based architecture using vector databases like FAISS, Pinecone, or Weaviate.
• Expertise in Vision Transformers, YOLO, Detectron2, and computer vision techniques.
• Familiarity with multi-agent architectures, React agents, and building intelligent UIs with frontend-backend synergy.
• Working knowledge of AWS services (SageMaker, Lambda, EC2, S3) and MLOps workflows (CI/CD for ML).
• Experience deploying and maintaining models in production environments.

• Experience with edge AI, NVIDIA Jetson, or industrial IoT integration.
• Prior involvement in developing AI-powered chatbots or assistants with memory and tool integration.
• Exposure to containerization (Docker) and model versioning tools like MLflow or DVC.
• Contributions to open-source AI projects or published research in AI/ML.

(ref:hirist.tech)