Quantitative Developer

About the Role

As a Quantitative Developer / Research Engineer, you will be an early member of the team with meaningful ownership of its systems, research tooling, and engineering practices. You will work closely with experienced researchers and trading-system engineers across the team and the firm, combining substantial autonomy with strong technical mentorship. You will work at the intersection of quantitative research and software engineering, turning research ideas into reliable systems that trade. This role requires you to be in the NY office 5 days per week.

• Design and build the core research and trading platform, including data pipelines, backtesting and simulation frameworks, portfolio and execution tooling, and research APIs
• Work closely with quantitative researchers to implement studies, test hypotheses, and translate promising ideas into robust production systems
• Develop and productionize statistical and machine learning models, owning the workflow from feature generation and training through backtesting, deployment, and live monitoring
• Build reliable data infrastructure for large historical and real-time datasets, with an emphasis on point-in-point correctness, reproducibility, performance, and ease of use
• Improve the performance and scalability of computationally intensive research and production workloads
• Contribute to foundational architecture and engineering decisions, working with experienced trading-system engineers to establish the development practices, testing standards, and operational processes the team will use as it grows
• Take systems and strategies from prototype to production and remain accountable for their reliability once they are live

Because the team is still early, the scope is broad and the feedback loop is short. You will have the opportunity to take on meaningful responsibility early, while learning from people with deep experience in quantitative research, trading-system architecture, and production trading.

Requirements

• A bachelor's, master's, or PhD degree in computer science, computer engineering, or another technical field
• At least two years of experience developing production software, primarily in Python and/or C++, with the ability and willingness to work across languages when needed
• Strong computer science fundamentals and sound instincts in software design, debugging, testing, and performance analysis
• The ability to enter an unfamiliar system, develop a clear mental model of it, and identify practical ways to improve its reliability, simplicity, and performance
• Fluency in a UNIX/Linux environment and a working understanding of operating systems, concurrency, networking, and system performance
• A track record of scoping and delivering production systems in fast-moving or ambiguous environments
• High ownership, good judgment, and a bias toward action—you identify risks early, reduce unnecessary complexity, and take pride in building systems that others rely on
• Clear communication and a collaborative working style, particularly when working across research and engineering disciplines

Experience in trading or finance is not required. We value strong engineering and problem-solving ability and will provide the domain-specific training needed to succeed.

Nice to Have

• Experience developing deep learning systems with PyTorch
• Experience with GPU computing, kernel development, distributed training, or performance optimization
• Hands-on experience building and operating machine learning or data pipelines in production
• Experience developing large-scale, concurrent, high-throughput, or performance-sensitive systems
• A strong foundation in mathematics, statistics, optimization, or machine learning
• Experience building tools and infrastructure for quantitative researchers, data scientists, or similarly technical users

Why This Role

• Build from an early stage — Help shape a new systematic trading business, with broad scope, short feedback loops, direct influence over how the team operates, and the opportunity to share in its success
• Autonomy with mentorship — Make meaningful technical decisions while learning from experienced researchers and trading-system engineers across the team and the firm
• Broad, end-to-end ownership — Take systems from research and development through deployment and live trading, working across software, data, machine learning, and financial markets
• AI-native engineering — Work in an environment where AI-assisted coding, testing, and research are deeply embedded in the development workflow

Pay

The annual base salary range for this position is $175,000 to $250,000 depending on the candidate’s experience, qualifications, and relevant skill set. The position is also eligible for an annual discretionary bonus.

Benefits

• Group medical, pharmacy, dental, and vision insurance
• 401k (with discretionary employer match)
• Short and long-term disability insurance
• Life and AD&D insurance
• Health savings accounts
• Flexible spending accounts