Junior AI

# Junior AI / Machine Learning EngineerFull-time (Singapore)Apply## The roleWe are looking for a Junior AI / Machine Learning Engineer to join our team straight out of university. In this role, you will work with senior AI engineers and data scientists to build, integrate, and improve AI-powered features in our products — from LLM-based assistants and retrieval-augmented generation (RAG) systems to classical ML models. This is a learning-focused role: we care more about your fundamentals, curiosity, and ability to learn quickly than about prior industry experience.##

What you'll do
* Model Development & Experimentation: Support the development, training, and evaluation of machine learning models under the guidance of senior engineers.
* LLM & Prompt Engineering: Help design, test, and iterate on prompts and pipelines for large language model use cases such as chatbots, summarisation, and classification.
* AI Feature Integration: Integrate AI capabilities into applications by building APIs, services, and workflows that connect models to product features.
* Data Preparation: Clean, label, and analyse datasets to support model training, evaluation, and ongoing quality improvements.
* Evaluation & Monitoring: Help build evaluation harnesses, run benchmarks, and monitor production AI features for accuracy, latency, and cost.
* Tooling & Automation: Contribute to internal tools, notebooks, and scripts that speed up experimentation and model iteration.
* Documentation: Document experiments, model behaviours, and integration steps so findings can be reproduced and shared.
* Continuous Learning: Keep up with new models, papers, and frameworks; share learnings with the team through internal demos and discussions.## What we're looking for
* A bachelor's or master's degree in Computer Science, Data Science, AI/Machine Learning, Statistics, or a related field (recent graduate or graduating within the next 6 months).
* Strong programming fundamentals in Python.
* Foundational understanding of machine learning concepts: supervised vs. unsupervised learning, training/validation/test splits, overfitting, and basic evaluation metrics.
* Exposure to common ML/DL libraries such as scikit-learn, PyTorch, or TensorFlow through coursework or personal projects.
* Comfortable with data manipulation libraries such as Pandas and NumPy.
* Familiarity with Git and collaborative development workflows.
* Strong problem-solving skills, intellectual curiosity, and the ability to communicate technical ideas clearly.
* Blockchain experience is a must.## Preferred Qualifications
* Personal projects, capstone work, or competitions (e.g., Kaggle) involving ML, NLP, or computer vision.
* Exposure to LLM tooling such as the OpenAI API, Anthropic API, Hugging Face Transformers, or LangChain / LlamaIndex.
* Familiarity with vector databases (e.g., Pinecone, Weaviate, pgvector) or basic RAG concepts.
* Basic experience building REST APIs (e.g., FastAPI, Flask) to serve model outputs.
* Awareness of MLOps concepts: experiment tracking, model versioning, and deployment (Docker, basic CI/CD).
* Exposure to cloud platforms (AWS, Azure, or GCP) is a plus.
* Strong written and verbal communication skills, and a thoughtful approach to AI safety and responsible use.##

How to apply
Email with the role title in the subject line. Attach your CV (PDF preferred) and a short note — one or two paragraphs — covering why this role and what you've built that you're proud of. Links to repos, products, or writing welcome. We read everything; expect a reply within five business days.11 Collyer Quay #16-02 The Arcade,Singapore