Gen AI Developer

Generative AI / Machine Learning Engineer (2-5 Years Experience)

Cloudbc Labs is seeking a highly motivated Generative AI / Machine Learning Engineer with 2-5 years of hands-on experience in LLMs, Deep Learning, and modern AI frameworks to join our team in Bangalore (Remote). This role involves designing, developing, and deploying scalable AI solutions, focusing on cutting-edge GenAI, Agentic AI, NLP, and Computer Vision use cases. You will collaborate closely with data scientists, product managers, and cloud engineers to drive innovation in artificial intelligence.

Key Responsibilities

• Design, develop, and deploy Generative AI and Machine Learning models for real-world applications.
• Build and optimize LLM-based solutions using frameworks like LangChain and LangGraph.
• Develop Agentic AI workflows and multi-agent systems.
• Implement NLP pipelines for text generation, summarization, classification, and retrieval (RAG).
• Work on Deep Learning and Neural Network architectures using PyTorch.
• Build and expose ML/AI services using FastAPI.
• Deploy and manage models on Azure and/or AWS cloud platforms.
• Develop Computer Vision models for image/video analysis as needed.
• Implement MLOps pipelines for training, versioning, monitoring, and CI/CD of models.
• Perform model evaluation, tuning, and performance optimization.
• Collaborate with cross-functional teams to translate business problems into AI solutions.
• Stay updated with the latest advancements in GenAI, LLMs, and AI research.

Required Skills & Qualifications

Core Technical Skills

• Strong proficiency in Python.
• Solid understanding of Machine Learning, Deep Learning, and Neural Networks.
• Hands-on experience with Large Language Models (LLMs).
• Experience in Natural Language Processing (NLP) techniques.
• Practical knowledge of PyTorch.
• Experience with LangChain and LangGraph.
• Familiarity with Agentic AI concepts and implementations.
• Experience building APIs using FastAPI.

Cloud & Deployment

• Hands-on experience with Azure and/or AWS.
• Experience deploying ML models in production environments.
• Knowledge of containerization tools (Docker preferred).

MLOps & Engineering

• Experience with MLOps practices (model versioning, monitoring, retraining).
• Understanding of CI/CD pipelines for ML systems.
• Knowledge of data pipelines and feature engineering.

Good to Have (Preferred Skills)

• Experience with RAG (Retrieval-Augmented Generation) systems.
• Knowledge of vector databases (FAISS, Pinecone, etc.).
• Experience in Computer Vision tasks (CNNs, image classification, object detection).
• Familiarity with Transformers architecture.
• Exposure to open-source LLMs (LLaMA, Mistral, etc.).
• Experience working in agile development environments.

Educational Qualification

• Bachelors or Masters degree in Computer Science, Data Science, AI, or a related field.