Data Scientist

Job Description – AI/ML Engineer (GenAI | Agentic AI | Computer Vision | Cloud) We are looking for passionate and highly skilled AI/ML Engineers to join our growing team and work on next-generation AI solutions across Generative AI, Agentic AI, and Computer Vision domains. This role is ideal for candidates who enjoy solving complex business problems using cutting-edge technologies and building scalable, production-ready AI systems. As an AI/ML Engineer, you will be responsible for designing, developing, and deploying intelligent applications leveraging Large Language Models (LLMs), AI Agents, Machine Learning, and Computer Vision techniques. You will collaborate closely with cross-functional teams to build innovative solutions that create real business impact. Key Responsibilities: Design and develop scalable AI/ML solutions using Generative AI, Agentic AI, and Computer Vision technologies Build intelligent AI agents and workflow automation systems using LLM frameworks Develop and optimize machine learning and deep learning models for production environments Work on image processing, object detection, OCR, classification, segmentation, and related Computer Vision use cases Build and manage end-to-end ML pipelines, model deployment, and monitoring systems Integrate AI solutions with cloud ecosystems such as Azure, AWS, or GCP Utilize Databricks and modern data platforms for large-scale data processing and model training Collaborate with product, engineering, and business teams to translate requirements into AI-driven solutions Ensure performance optimization, scalability, reliability, and security of deployed models Required Skills: Strong experience in Python programming and AI/ML development Hands-on experience with Generative AI, LLMs, and Agentic AI frameworks Experience with Computer Vision libraries and frameworks such as OpenCV, YOLO, TensorFlow, or PyTorch Good understanding of machine learning algorithms, deep learning, and MLOps practices Experience with cloud platforms such as Azure, AWS, or GCP Working knowledge of Databricks and distributed data processing Familiarity with APIs, vector databases, RAG pipelines, prompt engineering, and model fine-tuning Strong coding, debugging, and problem-solving abilities Preferred Qualifications: Experience with LangChain, CrewAI, AutoGen, Hugging Face, or similar AI frameworks Exposure to model deployment tools such as Docker and Kubernetes Understanding of CI/CD pipelines and production-grade AI systems Excellent communication and stakeholder management skills Experience: 3–10 Years Preferred Candidates: Immediate joiners or candidates currently serving notice period will be preferred.