Job Title

Cloudcraftz is a Singapore/India-based boutique quantitative research and applied AI company working with leading financial institutions, hedge funds, and asset managers. We build production-grade quantitative, machine learning, and AI-driven systems for trading, risk, and financial analytics, combining rigorous research with strong engineering.Job Summary:You will work in our Quantitative Finance and Applied AI practice, focused on building machine learning models for financial market prediction and enhancing them with unstructured data using modern AI approaches. This role sits at the intersection of traditional ML, financial time-series modeling, and emerging AI agent-based systems. You will contribute to research and prototyping of models and agentic workflows used in real-world financial applications.You should have 2–4 years of hands-on experience in machine learning, data science, or quantitative roles, preferably in finance or market-related domains, along with a solid understanding of financial markets, instruments, and time-series data. You are expected to have a strong foundation in machine learning, including regression and classification methods, tree-based models, basic deep learning, and sound model validation practices, and be highly proficient in Python and common data and ML libraries such as NumPy, pandas, scikit-learn, and PyTorch. You should be comfortable working with large datasets and building data pipelines for analysis and experimentation as well as having some exposure to using LLMs for processing unstructured text data. Exposure to AI Agent workflow development using LLMs and popular agentic frameworks is not a must but will be preferred. Strong problem-solving ability, curiosity, comfort with ambiguity, and clear written and verbal communication skills are essential for success in this role.Employment Type: Full-timeLocation: The initial location for this role will be with the practice in Bengaluru. We are expanding our teams in Singapore; subsequent moves to this location will be possible for the right candidates.Notice Period: 30 days/currently serving notice