ML Researcher / Modeling Quant

Company Description

BHFT is a proprietary algorithmic trading firm. Our team manages the full trading cycle, from software development to creating and coding strategies and algorithms.

Our trading operations cover key exchanges. The firm trades across a broad range of asset classes, including equities, equity derivatives, options, commodity futures, rates futures, etc. We employ a diverse and growing array of algorithmic trading strategies, utilizing both High-Frequency Trading (HFT) and Medium-Frequency Trading (MFT) approaches.

Looking ahead, we are expanding into new markets and products. As a dynamic company, we continuously experiment with new markets, tools, and technologies.

We've got a team of 200+ professionals, with a strong emphasis on technology-70% are technical specialists in development, infrastructure, testing, and analytics spheres. The remaining part of the team supports our business operations, such as Risks, Compliance, Legal, Operations and more.

With a strong focus on innovation and performance, BHFT is actively expanding its presence in traditional financial markets. We value a results-driven culture, emphasizing collaboration, transparency, and constant improvement, all while offering the flexibility of remote work and a globally distributed team.

Job Description

We are hiring an ML Researcher / Modeling Quant to accelerate the process of turning research into production-ready models. This role is about speed, precision, and teamwork -designing, training, and optimizing predictive models under real trading constraints . You'll be the bridge between alpha discovery and execution, ensuring our signal library is transformed into strategies that can run stably and efficiently at scale .

Key Responsibilities

• Research, develop, and rapidly prototype advanced ML models to drive strategy performance across liquid markets.
• Design and optimize deep learning architectures that translate signals and features into actionable strategies.
• Evaluate and improve existing production models by refining parameterization, optimizing inference speed, and scaling training workflows.
• Own and maintain robust, automated ML pipelines for feature generation, training, retraining, and deployment-built to handle real-time market conditions.
• Collaborate tightly with alpha researchers, data engineers, and execution quants to ensure end-to-end integration of models .
• Anticipate and mitigate risks like overfitting, data leakage, and model drift before they impact performance.

Qualifications

Additional Information

What we offer :