Aquatic Capital Management

Research Engineer

Sea Girt, New Jersey, United States

Not SpecifiedCompensation
Junior (1 to 2 years), Entry Level & New GradExperience Level
Full TimeJob Type
UnknownVisa
AI & Machine Learning, Research, Software EngineeringIndustries

Requirements

Candidates should possess a Bachelor’s or Master’s degree in Computer Science, Applied Math, Engineering, or a related technical field, demonstrating strong software engineering skills with experience in machine learning, numerical computing, and/or applied ML research. Practical experience deploying ML models or infrastructure in a research and production environment is required, along with familiarity with Python and numerical/ML frameworks such as PyTorch, JAX, and numpy, and a plus for experience with PyTorch 2.x compiler stack technologies. Understanding of GPU architecture and profiling techniques is also beneficial.

Responsibilities

The Research Engineer will scale neural network training systems to support larger, more complex models while maintaining the ability to run many experiments simultaneously, explore and prototype novel modeling approaches, collaborate with researchers to integrate promising models into production, profile and optimize distributed model training and inference utilizing GPU acceleration and ML compiler technologies, and establish best practices for a clean, reproducible, and maintainable research codebase.

Skills

Python
PyTorch
JAX
numpy
GPU architecture
Profiling techniques
Distributed model training
ML compiler technologies

Aquatic Capital Management

Quantitative investment management for institutional clients

About Aquatic Capital Management

Aquatic Capital Management specializes in quantitative investment management, focusing on creating financial models that predict market movements. The company uses advanced research and development techniques, employing a team of skilled researchers and engineers to develop data-driven investment strategies for institutional clients like hedge funds and pension funds. Aquatic's products work by leveraging mathematical models and algorithms to analyze market data and generate insights that help clients maximize their returns. Unlike many competitors, Aquatic operates without the limitations of outdated systems, allowing for greater agility and responsiveness to market changes. The company's goal is to build the best prediction machine in the industry while fostering a collaborative and innovative workplace culture that attracts top talent.

Key Metrics

Chicago, IllinoisHeadquarters
2015Year Founded
VENTURE_UNKNOWNCompany Stage
Fintech, Quantitative FinanceIndustries
11-50Employees

Benefits

Vacation
Mentoring and development programs
Weekly happy hours
Daily catered meals

Risks

Competition from new hedge funds may challenge Aquatic's market position.
Brand confusion may arise from Motive Offshore's acquisition of Acteon's Aquatic business.
Regulatory scrutiny on quantitative strategies could increase compliance costs for Aquatic.

Differentiation

Aquatic leverages advanced R&D to create sophisticated financial models for market prediction.
The company operates without legacy constraints, allowing agility in market response.
Aquatic's culture attracts top talent with a focus on collaboration and innovation.

Upsides

Rising ESG investing interest could attract more institutional clients to Aquatic.
Alternative data sources enhance predictive accuracy in Aquatic's quantitative models.
Machine learning advancements align with Aquatic's focus, improving their competitive edge.

Land your dream remote job 3x faster with AI