ML Researcher for Market-Facing Deep Learning & Trading

Virtu Careers; New York (NY); On-site; USD 200,000 - 300,000; Full time

Job summary

Virtu Financial is seeking a Machine Learning Researcher to pursue high-impact research within a results‑oriented, agile organization. You’ll own the modeling ecosystem—from feature engineering to training dynamics and execution strategy—and your innovations will influence how we operate in markets globally.

A curious mindset, strong technical skills, and collaboration with traders, researchers, and developers are essential.

Qualifications

• Minimum 2 years of applied experience developing deep learning solutions.
• Proven ability to transfer ML methods across problem domains.
• Strong production mindset focused on delivering bottom-line value.
• Proficiency in rapid prototyping and iterative development in Python and DL frameworks.
• Experience with PyTorch/JAX development; production exposure to C++ is a plus.

Responsibilities

• Investigate, evaluate, and prototype innovative ML solutions using novel ML and deep learning techniques. Reinforcement learning experience is a bonus
• Develop deep learning models with direct impact on P&L and forecasting
• Implement ML approaches for forecasting, feature engineering, and optimization challenges
• Conduct empirical ML research across multiple problem domains with rapid prototyping of architectures
• Translate research methods into actionable data features and predictive models in collaboration with traders and developers

Skills

Applied ML

Deep learning

Python

Tools

PyTorch

TensorFlow

JAX

Job description

Virtu Financial is seeking a Machine Learning Researcher to pursue high-impact research within a results‑oriented, agile organization. You’ll own the modeling ecosystem—from feature engineering to training dynamics and execution strategy—and your innovations will influence how we operate in markets globally.

A curious mindset, strong technical skills, and collaboration with traders, researchers, and developers are essential.