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AI / ML Engineering Intern
Remote / Hybrid · 3–6 Months · Paid · Start: ASAP
About the Role
We're looking for a curious, technically sharp AI/ML Engineering Intern to work alongside our quant and data science team. You'll contribute to real production systems — not toy projects — touching everything from model development and backtesting to infrastructure and evaluation pipelines.
What You'll Work On
- Build, train, and evaluate ML models across structured and time-series datasets
- Develop and test quantitative signals, features, and factor libraries
- Instrument ML experiments with logging, metrics, and reproducible pipelines
- Assist in backtesting and validating predictive models against historical data
- Write clean, well-documented Python code that integrates into existing systems
- Explore LLM-based tooling for data extraction, summarisation, or research automation
Requirements
- Pursuing or recently completed a degree in CS, Statistics, Math, or related field
- Solid Python; comfortable with NumPy, pandas, scikit-learn
- Foundational ML knowledge — supervised/unsupervised, evaluation, overfitting
- Familiar with Git and version-controlled workflows
- Strong analytical thinking and attention to numerical detail
Nice to Have
- Experience with PyTorch or TensorFlow
- Exposure to time-series modelling (ARIMA, GARCH, etc.)
- Knowledge of financial data or markets
- Familiarity with MLflow, Weights & Biases, or similar
What We Offer
- Real ownership — your work ships to production
- Direct mentorship from senior quant & ML practitioners
- Async-friendly, outcome-oriented culture
- Access to tools, papers, and courses
To Apply: Send a brief note about yourself, a link to relevant work (GitHub, research, projects), and your availability.
Click on Apply to know more.