Principal Research Scientist - Time Series Transformer Models

[Recruiter-Jim]

Department: Deep Learning - Applied Research
Location: Austin / New York
Compensation: $750k - $1.5 million+ (Negotiable based on experience and impact)

My client is a leading quantitative trading firm pushing the boundaries of financial modeling in high frequency trading. They leverage petabytes of data (and growing!) to develop cutting-edge trading strategies. They foster a culture of innovation, collaboration, and intellectual curiosity, providing researchers with the freedom and resources to explore the most promising avenues in AI and machine learning.

About the Role:

We are seeking a world-class research scientist with deep expertise in time series analysis and transformer models to join an elite team of applied researchers.

In this role, you will:

• Collaborate: Work closely with a team of brilliant PhDs to design, implement, and evaluate novel transformer architectures for very long financial time series data.
• Innovate: Contribute to the development of cutting-edge models that can train and infer at scales 10-100x greater than financial industry standards, pushing the boundaries of what's possible at the intersection of AI in finance.
• Optimize: Develop and implement highly efficient training and inference strategies, achieving microsecond or nanosecond prediction times in our high-frequency trading environment.
• Discover: Work alongside the team to identify and extract novel predictive signals ("alpha") from petabytes of data.
• Impact: Directly contribute to the success of our trading strategies and shape the future of our firm.

Qualifications:

• Expert in Time Series Transformer Models.
• Deep understanding of time series analysis, forecasting.
• Extensive experience with transformer models and deep learning frameworks (e.g., JAX, TensorFlow, PyTorch).
• Strong track record of research publications in top AI conferences (e.g., NeurIPS, ICML, ICLR).
• Experience with very large datasets and distributed computing.
• Experiance solving scaling challenges. (very large models, very large data sets, implementing at scale)
• Excellent communication and collaboration skills.

Bonus Points:

• Experience with financial time series data and trading strategies. (orderbook, lead-lag, stat-arb etc).
• Expertise in high-performance computing and low-latency systems.
• Familiarity with acceleration techniques (e.g., CUDA, GPUs, FPGAs).

Benefits:

• Exceptional Compensation: Highly competitive salary and compensation with performance linked bonus.
• Unparalleled Resources: Access to vast datasets, powerful computing infrastructure, and the latest GPU's.
• Intellectual Freedom: Flexibility to pursue innovative research directions within a supportive and collaborative environment.
• Real-World Impact: See your research directly translate into trading outcomes and contribute to the success of a leading quantitative research firm.