ML Researcher / Modeling Quant

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.

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.

• Master’s or PhD in Applied Mathematics, Statistics, Physics, Engineering, Financial Engineering, Computer Science, or related field from a top-tier institution.
• 5+ years of hands-on ML modeling experience, ideally within trading, fintech, or similarly time-critical domains.
• Expertise in modern ML techniques (Deep Learning, Reinforcement Learning, LLMs) with a focus on practical deployment.
• Advanced coding proficiency in Python and/or C++ with mastery of ML frameworks (PyTorch, TensorFlow).
• Demonstrated ability to deploy models in production under latency-sensitive conditions.
• Strong collaborator who communicates clearly across teams and moves fast without sacrificing quality.
• Proactive, self-motivated, and committed to execution speed and reliability.

What we offer:

• Experience a modern international technology company without the burden of bureaucracy.

• Collaborate with industry-leading professionals, including former employees of Tower, DRW, Broadridge, Credit Suisse, and more.

• Enjoy excellent opportunities for professional growth and self-realization.

• Work remotely from anywhere in the world with a flexible schedule.

• Receive compensation for health insurance, sports activities, and non-professional training.