AI Engineering Intern

Location: Singapore Duration: Minimum 6 months About the Role CloudMile is looking for an AI Engineering Intern to help design, build, and deploy Generative AI applications and machine learning solutions for real-world business use cases. You will gain hands-on experience across the AI application lifecycle—from data preparation and model development to backend integration, evaluation, and cloud deployment. Projects may involve large language models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, conversational AI, and machine learning models . This role is ideal for someone who wants to move beyond experimentation in notebooks and develop practical, production-ready AI applications. Key Responsibilities Design and develop Generative AI applications , including RAG systems, AI agents, enterprise search, and conversational AI solutions. Build, train, evaluate, and improve machine learning models for use cases such as classification, prediction, recommendation, and natural language processing. Develop and integrate AI services using Python and backend frameworks such as FastAPI . Work with LLM frameworks and tools such as LangChain, LangGraph, Vertex AI, and Dialogflow . Perform data preparation, feature engineering, vector embedding, semantic search, and model evaluation. Develop effective prompts and improve LLM responses through prompt engineering, retrieval optimization, and evaluation. Support the development of end-to-end AI applications, including integration with frontend applications built using React or Next.js . Deploy and operate AI workloads on Google Cloud , using services such as Vertex AI, BigQuery, Cloud Run, and Cloud Storage. Collaborate with engineers to prototype, test, document, and deploy AI features. Research emerging AI technologies and assess their suitability for enterprise use cases. Requirements Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related discipline. Strong programming foundation in Python . Practical experience with at least one of the following: Building Generative AI or LLM-powered applications Developing or evaluating machine learning models Creating APIs or backend services Familiarity with fundamental machine learning concepts, including training, validation, evaluation metrics, and model performance. Basic understanding of LLMs, RAG, prompt engineering, or conversational AI. Comfortable using Git and working in a collaborative development environment. Strong analytical and problem-solving skills, with the ability to learn new technologies quickly. Able to work independently while collaborating effectively with a technical team. Nice to Have Experience with FastAPI, React, Next.js, LangChain, LangGraph, or Dialogflow . Familiarity with machine learning frameworks such as scikit-learn, PyTorch, or TensorFlow . Experience with embedding models and vector databases such as FAISS, Pinecone, Weaviate, or pgvector . Exposure to Google Cloud , Docker, Kubernetes, CI/CD, MLOps, or model deployment. Experience evaluating LLM applications for accuracy, groundedness, safety, latency, and cost. Previous AI-related internships, academic research, hackathons, personal projects, or open-source contributions. A portfolio or GitHub repository demonstrating AI or software development projects. Why Join CloudMile? Work on real-world AI projects with experienced AI and cloud engineers. Gain practical experience building end-to-end, production-ready AI applications . Learn how Generative AI and machine learning solutions are designed and deployed in enterprise environments. Gain exposure to modern AI frameworks and Google Cloud technologies. Receive mentorship, technical guidance, and opportunities to develop your engineering skills. Work in a collaborative, dynamic, and supportive regional team. If you are passionate about AI and enjoy turning ideas and models into working applications, we would love to hear from you.