AI / ML Fresh Graduates for Intership

fresh graduates in AI/ML

3-month paid internship

What We’re Looking For

builders

You are a strong fit if you are:

Kaggle-Caliber Talent

• Expert-level skills demonstrated by Kaggle competitions, notebooks, or ML pipelines.
• Ability to clean, engineer, and synthesize complex, messy datasets.
• Experience with model stacking/ensembles, feature engineering, and experimental design.

AI Fluency in the Financial Sector

(You don’t need professional experience, but must be deeply knowledgeable.)

You should understand:

• Market prediction tasks (classification/regression, forecasting, volatility modeling)
• Options Greeks, volatility modeling, order flow, microstructure, etc. (big advantage)
• How to evaluate models with financial metrics (Sharpe, drawdown, expectancy)
• Handling non-stationary data, regime shifts, and walk-forward testing

Strong Engineering Skills

• Python (NumPy, Pandas, Scikit-Learn, PyTorch/TF/JAX)
• Experiment tracking (MLflow, Weights & Biases)
• Writing clean, modular research code

Responsibilities

During the 3-month internship you will:

AI Research

• Build predictive ML models for equities, options, and market microstructure.
• Develop novel features (e.g., volatility signals, flow metrics).
• Create ensemble models combining classifiers, regressors, and time-series architectures.
• Implement backtesting and simulation frameworks for predictive signals.

Data Engineering

• Work with large, noisy, real-time financial datasets.
• Automate data pipelines, cleaning, normalization, and labeling.
• Experiment with feature extraction, including deep learning embeddings.

Quant Insights & Reporting

• Analyze model performance across regimes and market conditions.
• Present weekly research findings and model improvements.
• Generate explainability reports (SHAP, ICE plots, feature attributions).

What You Will Learn

• Professional quant research methodology
• Walk-forward validation & avoiding look-ahead bias
• How institutions use AI for market prediction
• Real-time model deployment
• Building production-ready financial AI systems
• Advanced feature engineering from financial microstructure

Requirements

Mandatory

• Bachelor’s degree in CS, Data Science, Math, Engineering, or related field
• Kaggle experience (notebooks, competitions, or pipelines)
• Strong Python + ML fundamentals
• Knowledge of financial markets & AI applications in finance

Bonus Skills

• Experience with deep learning for tabular/time-series data
• Understanding of derivatives (gamma, vanna, skew, etc.)
• Quant research exposure through university projects or competitions

💼 What You Get

• Paid 3-month internship

• Direct mentorship from senior AI/quant leaders

• Real, production-level financial datasets

• Weekly research sprints

• State-of-the-art tools & GPU compute

• Full-time job opportunity upon successful completion

• (We hire every intern who meets performance standards — high performers are fast-tracked.)