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.