Machine Learning (ML) Researcher

Flumen is on the quest for a highly skilled Machine Learning Researcher to spearhead innovations in our high-frequency trading (HFT) systems. This pivotal position is dedicated to the creation and implementation of sophisticated ML models aimed at refining trading strategies, reducing response times, and maximizing financial outcomes. The ideal candidate will become an integral member of our ML research team, tasked with devising algorithms that harness the power of real-time market data for swift predictive analytics and trading execution.

Key Responsibilities

Design, test, and implement ML algorithms specifically crafted for HFT.
Collaborate extensively with multidisciplinary teams to seamlessly integrate ML models into our trading infrastructure.
Analyze large datasets to extract valuable trading insights and enhance algorithmic tactics.
Stay ahead of the curve in ML and fintech innovations to ensure
Flumen remains at the forefront of the industry.

Essential Skills and Qualifications

A minimum of 5 years’ experience in developing ML models, preferably within the HFT.
Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field is a must; a Ph.D. is highly desirable.
Proficiency in machine learning programming languages, especially Python; knowledge of C++ is a plus.
Comprehensive expertise in ML algorithms and platforms, with a preference for PyTorch, but also including TensorFlow and/or JAX.
Outstanding analytical skills, with a proven ability to process complex datasets into tangible trading advantages.
Exceptional communication and interpersonal skills, fostering a team-oriented and collaborative work environment.

Benefits

Competitive compensation package, including discretionary bonuses.
Comprehensive health benefits (medical, dental, vision).
Employer-funded life insurance.
Generous vacation policy and a commitment to work-life balance.

Apply Now

Join Flumen to contribute to the cutting edge of financial trading technology.

Flumen