Quantitative Developer

DRW is building a new systematic, mid-frequency trading business. The Quantitative Developer / Research Engineer will build research and trading systems, work with quantitative researchers to develop and productionize strategies, and support reliable data infrastructure and live trading.

Responsibilities

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-time 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

Preferred

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

Deep Learning

PyTorch

GPU Computing

Kernel Development

Distributed Training

Performance Optimization

Production ML Pipelines

Data Pipelines

Large-Scale Systems

Concurrent Systems

High-Throughput Systems

Performance-Sensitive Systems

Mathematics

Statistics

Optimization

Machine Learning

Research Tools Development

Infrastructure Development

Quantitative Research

Data Science

Benefits

The position is also eligible for an annual discretionary bonus.

Group medical, pharmacy, dental and vision insurance

401k (with discretionary employer match)

Short and long-term disability

Life and AD&D insurance

Health savings accounts

Flexible spending accounts

Company

Diversified global trading and investment firm

Chicago, Illinois, USA

http://drw.com/

Founded in 1992

1001-5000 employees

Qualifications

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 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

Required skills

C++, Concurrency, Debugging, Distributed Training, GPU Computing, Kernel Development, Machine Learning, Operating Systems, Performance Analysis, PyTorch, Python, Represents the skills you have, Software Design, Software Testing, System Performance, UNIX/Linux, click on the tags

Preferred skills

Experience developing deep learning systems with PyTorch

Experience

2+ years