Quantitative Developer - Systematic Research Technology

Balyasny Asset Management L.P.; New York (NY); On-site; USD 180,000 - 240,000; Full time

Job summary

Balyasny Asset Management L.P. is seeking exceptional engineers to build the quantitative research and trading systems behind systematic investing. The role spans Python and C++, with Python for research workflows and C++ for performance-critical production code.

You will work with Portfolio Managers, Quant Researchers, and Technologists, taking ownership from design through deployment and production operation. The work emphasizes reliability, observability, and scalable solutions.

Qualifications

• 5+ years of hands-on development experience.
• Strong experience in Python, C++, or both.
• Exceptional programming ability and fundamentals.
• Degree in CS/Engineering/Math/Stats/Physics or equivalent.

Responsibilities

• Design, build, and own software for quantitative research and trading.
• Develop Python tooling and libraries to speed up research.
• Build and improve C++ components for performance-sensitive workflows.
• Collaborate with researchers to translate needs into durable solutions.
• Improve reliability, observability, and testability of systems.
• Diagnose complex problems across research to production.
• Contribute to high engineering standards through code reviews.

Skills

Python

C++

Software engineering

Communication

Education

CS/Engineering/Math/Stats/Physics degree

Tools

Linux

Job description

A role spanning Python and C++ for exceptional engineers who want to build the quantitative research and trading systems behind systematic investing.

About the Role

Systematic Research Technology builds research and trading systems that enables systematic investment teams to discover, evaluate, and deploy investment ideas. We work on technically demanding problems where engineering quality directly affects research velocity, system reliability, and the ability to operate at scale.

We are looking for exceptional engineers who want to apply strong software engineering judgment to quantitative investing. You will work closely with Portfolio Managers, Quantitative Researchers and Technologists, owning meaningful technical problems from initial design through deployment and production operation.

This role spans Python and C++. Python is used extensively for research workflows, data-intensive analysis, and developer tooling. C++ is used for performance-sensitive and production-critical systems. We welcome engineers with strength in one language who have the ability and interest to work productively across both.

What You Will Do

• Design, build, and own software that supports quantitative research, data processing, model evaluation, and systematic trading.
• Develop Python tooling and libraries that make research faster, more reproducible, and easier to scale.
• Build and improve C++ components for performance-sensitive and production-critical workflows.
• Partner directly with Quantitative Researchers to turn complex and often ambiguous research needs into durable technical solutions.
• Improve the reliability, observability, testability, and operational quality of research and production systems.
• Diagnose difficult technical problems across the research-to-production lifecycle and make pragmatic architecture decisions.
• Contribute to a high engineering bar through thoughtful design, code review, testing, and knowledge sharing.

What We Are Looking For

• 5+ years of hands-on development experience building and supporting production systems.
• Strong experience in Python, C++, or both, and the ability and interest to work productively across both languages.
• Exceptional programming ability and strong software-engineering fundamentals.
• Sound judgment in software design, debugging, performance analysis, testing, and maintainability.
• Experience building data-intensive, performance-sensitive, or production-critical systems.
• Curiosity, ownership, and the ability to learn unfamiliar technical or business domains quickly.
• Ability to communicate clearly and work effectively with Portfolio Managers, Quantitative Researchers, Technologists, and other stakeholders.
• A degree in Computer Science, Engineering, Mathematics, Statistics, Physics, or a related field, or equivalent practical experience.

Helpful, but Not Required

• Experience with systematic investing, quantitative finance, market data, or time-series analysis.
• Experience with Linux, distributed systems, GPUs, cloud infrastructure, data platforms, or low-latency systems.
• Familiarity with numerical computing, simulation, optimization, machine learning, or large-scale data processing.