Research Engineer

Aquatic was founded with a shared passion for tackling some of the most complex challenges in one of the world’s most competitive arenas—global financial markets. From the very beginning, we have been driven by a deep commitment to applying cutting-edge scientific research and technological innovation to deliver unparalleled performance. Our journey is one of continuous growth and exploration, marked by a spirit of curiosity and relentless drive for excellence. 

Aquatic Capital Management is seeking a Research Engineer to join our research team. Your work will blend software engineering and quantitative research, focusing on designing high-performance tooling and infrastructure that accelerate the development of machine learning models used in systematic trading.

You will work closely with quantitative researchers to build the next generation of modeling platforms —from applying numerical computation methods, to training deep learning models. The software you develop will play a central role in driving the firm’s machine learning strategy.

Role Details:

• Scale neural network training systems to support larger, more complex models while maintaining the ability to run many experiments at once


• Explore and prototype novel modeling approaches (e.g., more efficient decision trees, the latest transformer variant)


• Collaborate with researchers to take promising models quickly and reliably into production


• Profile and optimize distributed model training and inference–for example, by using GPU acceleration and the latest ML compiler technologies.


• Establish best practices for a clean, reproducible, and maintainable research codebase where new ideas can be quickly validated.

Technical Experience:

• Strong software engineering skills with experience in machine learning, numerical computing, and/or applied ML research


• Proficiency with Python and numerical + ML frameworks (PyTorch, JAX, numpy), familiarity with PyTorch 2.x compiler stack (e.g., TorchScript, TorchInductor) is a plus


• Practical experience deploying ML models or infrastructure in a research and production environment


• Understanding of GPU architecture (memory structure, SMs, performance counters, etc.) and profiling techniques a plus


• BS/MS/PhD in Computer Science, Applied Math, Engineering, or a related technical field

Candidate Qualities:  

• Strong bias for action


• Driven by accountability and internal urgency


• Desire to independently seek best solutions


• Preference for working in a team that focuses on delivering results aligned with Research goals


• Comfortable providing and receiving actionable feedback in a collaborative team setting


• Motivated by an ambitious environment and driven colleagues 

The base salary for this role is anticipated to be between $150,000 and $300,000, which is based on information at the time of posting. This position may also be eligible for additional forms of compensation, such as a discretionary bonus, and benefits. Discretionary bonus can be a significant portion of total compensation. Actual compensation for successful candidates will be carefully determined based on a number of factors, including their unique skills, qualifications and relevant experience.

Benefits:

• Benefits: For full-time employees, fully paid medical, dental, and vision for employees and dependents, competitive 401k plan, employer-paid life & disability insurance 


• Perks: Wellness programs, casual dress, snacks, lunch, game room, team and company events


• Development: Open environment to maximize learning and knowledge sharing


• Time: Generous PTO, paid holidays, competitive paid caregiver leaves

Aquatic Capital

This role represents a unique opportunity to join a quantitative investment manager in its early stage of growth. The firm’s culture will be shaped by collaboration, meritocracy, ambition, and calm determination.

Aquatic is a proud equal opportunity workplace. We do not discriminate based upon race, religion, color, national origin, sex, sexual orientation, gender identity/expression, age, status as a protected veteran, status as an individual with a disability, or any other applicable legally protected characteristics.