We are looking for a skilled AI Engineer with 2–5 years of experience to join our engineering team. The ideal candidate should have hands-on experience in Artificial Intelligence, Machine Learning, Python, Generative AI, and AI/ML frameworks. You will be responsible for designing, developing, and deploying AI-driven solutions that solve real-world business problems.

Please read the job criteria below and drop us an email at joinus@tudip.com OR create an account on our Recruitment Portal to get started.

• Design, develop, and deploy AI/ML models and applications.
• Develop AI solutions using Python and relevant AI/ML frameworks.
• Work with Generative AI, LLMs, prompt engineering, and AI-powered applications.
• Build and integrate REST APIs for AI/ML solutions.
• Perform data preprocessing, feature engineering, model training, and evaluation.
• Fine-tune and optimize machine learning and deep learning models.
• Work with LLMs and frameworks such as LangChain, LlamaIndex, or similar technologies.
• Develop RAG (Retrieval-Augmented Generation) based applications and integrate vector databases.
• Integrate AI solutions with existing applications and third-party services.
• Monitor model performance and troubleshoot AI/ML applications in production.
• Collaborate with software developers, data scientists, product teams, and other stakeholders.
• Stay updated with the latest developments in Generative AI, LLMs, Machine Learning, and AI engineering.

• 2–5 years of hands-on experience in AI/ML Engineering or a related field.
• Strong programming skills in Python.
• Good understanding of Machine Learning and Deep Learning concepts.
• Experience with frameworks such as TensorFlow, PyTorch, Scikit-learn, or equivalent.
• Hands-on experience with Generative AI and Large Language Models (LLMs).
• Knowledge of Prompt Engineering and LLM integration.
• Experience with RAG, embeddings, vector databases, and semantic search.
• Experience working with REST APIs and AI/ML model integration.
• Good understanding of data structures, algorithms, and software development practices.
• Familiarity with Git and CI/CD processes.

• Experience with OpenAI, Azure OpenAI, Gemini, Claude, or other LLM APIs.
• Experience with vector databases such as Pinecone, FAISS, Weaviate, or ChromaDB.
• Knowledge of AWS, Azure, or GCP AI/ML services.
• Experience with Docker and Kubernetes.
• Knowledge of MLOps and model deployment.
• Experience building AI chatbots, AI agents, recommendation systems, or document intelligence solutions.

Education