Junior ML Engineer

Role Overview

We are looking for a Machine Learning Engineer to design, build, and deploy ML models for stock market analytics, trading strategies, and risk management. You will work closely with quant researchers, data engineers, and traders to convert research models into scalable, production-grade systems.

Key Responsibilities

- Develop and deploy ML models for price prediction, volatility forecasting, alpha generation, signal optimization, and market anomaly detection.

- Work with time-series data (tick, minute, OHLC, order book).

- Implement deep learning models (LSTM, GRU, Transformers, attention-based architectures).

- Optimize models for low latency and high throughput.

- Design model training, evaluation, and backtesting pipelines.

- Deploy models using REST APIs or streaming frameworks.

- Monitor model performance, drift, and retraining cycles.

Required Skills

- Strong proficiency in Python and ML libraries (NumPy, Pandas, Scikit-learn).

- Hands-on experience with TensorFlow or PyTorch.

- Solid understanding of time-series forecasting.

- Experience with feature engineering for financial data.

- Knowledge of model evaluation metrics for trading systems.

- Familiarity with Git, Docker, and CI/CD.

Good to Have

- Experience with algorithmic trading or quantitative finance.

- Knowledge of reinforcement learning.

- Exposure to cloud platforms (GCP).

- Understanding of market microstructure and order books.

What We Offer

- Opportunity to work on real-time trading systems.

- Access to large-scale financial datasets.

- High-performance computing environment.

- Competitive compensation and performance-based bonuses.