Senior Deep Learning Researcher

We are seeking a highly motivated and skilled Senior Deep Learning Researcher to join our team. This individual will have the opportunity to contribute to cutting-edge research in artificial intelligence and machine learning. The ideal candidate will be prepared to work independently as an individual contributor (IC) for at least one year, engaging in high-level research activities aimed at advancing the HFT field.

Responsibilities

• Conduct original research in the areas of artificial intelligence, machine learning, and related quantitative fields;
• Develop and experiment with modern deep learning architectures;
• Analyse large, unstructured, and noisy datasets to extract meaningful insights;
• Continually explore new methodologies and technologies to enhance research outcomes.
  

Requirements

• Equivalent research experience such as published research findings in top-tier journals and conferences or a PhD / MD in Computer Science, Electrical Engineering, Mathematics, or a related quantitative discipline;
• Strong background in machine learning and mathematical statistics;
• Practical experience and a profound understanding of modern DL architectures, especially focusing on transformers and their variants;
• Proficient programming skills (any language, with Python being preferable);
• Hands-on experience of conducting high-quality research;
• Background in analysing large, unstructured, and noisy datasets;
• A PhD (in Computer Science, Electrical Engineering, Mathematics, or a related quantitative discipline) or equivalent research experience.
  

What we offer

• High base salary and social benefits;
• Generous bonus structure. We are very flexible in discussing salary and conditions of employment;
• Cutting-edge hardware and software in production as well as high technical expertise of the company which allows implementation of bold ideas and boosting great results. Ownership over initiatives that directly solve business problems;
• Ability to trade on dozens of international exchanges;
• Flexible workflow (lack of formalism and bureaucracy, no pressure and over-management) and working schedule;
• Tuition reimbursement, conference and training sponsorship.