DRW is a global trading firm that leverages technology and research to capture diverse investment opportunities across various asset classes and markets.
Chicago, IL
At DRW, we identify and capture trading and investment opportunities globally. What sets us apart is our diversified approach—trading across many asset classes and instruments, in markets around the world, with horizons from seconds to years. We succeed by leveraging technology, research and risk management. We offer the best of both worlds: the opportunity and spirit of a startup and the benefits and stability of an established, experienced firm. Our employees work hard to solve interesting problems, and their results are rewarded. We value continuous learning—from our outcomes, from the environment and from each other. It’s a place of high expectations, deep curiosity, and constant collaboration, with some of the smartest, most passionate people you’ll meet. // Chez DRW, nous identifions et saisissons les opportunités de négociation et d'investissement au niveau mondial. Ce qui nous différencie, c'est notre approche diversifiée : nous négocions sur de nombreuses classes d'actifs et d'instruments, sur des marchés du monde entier, avec des horizons allant de quelques secondes à plusieurs années. Nous réussissons en nous appuyant sur la technologie, la recherche et la gestion des risques. Nous offrons le meilleur des deux mondes: les opportunités et l'ésprit d’une entreprise en démarrage, et les avantages et la stabilité d'une entreprise établie et expérimentée. Nos employés travaillent dur pour résoudre des problèmes intéressants et leurs résultats sont récompensés. Nous valorisons l'apprentissage continu – de nos résultats, de l’environnement et de chacun de nous. C’est un lieu où les attentes sont élevées, la curiosité est profonde et la collaboration est constante, et où l’on retrouve quelques-uns des individus les plus intelligents et les plus passionnés que vous puissiez rencontrer.
On-site · Montréal
The Platform Engineer will build and operationalize an AI tooling ecosystem by integrating cloud AI providers, internal models, and end-user tools. Responsibilities include managing multi-engine API gateways, implementing routing rules, and ensuring secure governance of AI traffic.
On-site · Montréal
The Platform Engineer will build and operationalize an AI tool ecosystem by integrating external cloud providers, internal models, and end-user tools. Key tasks include managing API gateways, implementing routing logic, and ensuring secure governance of AI traffic across the enterprise.
On-site · Montréal
Configure and operate multi-provider AI API gateways, migrate enterprise AI tools into a centralized control plane, and manage AI services such as Azure OpenAI deployments in coordination with the cloud team. Develop Go and Python code for usage synchronization and automated alerts, and work with the inference infrastructure team to register and route internal models.
On-site · Montréal
The Platform Engineer will build and operationalize an AI tooling ecosystem by integrating external cloud AI providers and internal models. They will also manage multi-engine API gateways, implement routing rules, and ensure secure governance of AI traffic across the firm.
On-site · Montréal
You will build state-of-the-art data visualization and analysis tools to help traders extract insights from their trades. Additionally, you will implement scalable software to support data-driven decision-making across multiple trading desks.
On-site · Montréal
Design and develop scalable software tools for trading data analysis and visualization to support internal trading desks. Collaborate with quantitative analysts and traders to translate business needs into high-performance, maintainable technical solutions.
On-site · Montréal
Develop critical software for the collection, transformation, and delivery of market data used by trading systems. Collaborate with operations and trading teams to ensure production systems are optimized and lead new technical initiatives.
On-site · Montréal
You will develop and operate agentic systems and infrastructure to turn real-world events into actionable trading signals. This involves rapid analysis, building production-grade systems, and maintaining high-performance infrastructure from the network edge to in-memory stores.
On-site · Montréal
Design and implement scalable systems to serve machine learning models and optimize training and inference performance. Create feature pipelines and monitoring infrastructure while leading new initiatives and collaborating with stakeholders.
Hybrid · Montréal
You will design and build reliable backend services and infrastructure tooling while managing applications in a Kubernetes-based environment. Additionally, you will develop automation to improve deployment workflows and maintain CI/CD pipelines to support engineering teams.
On-site · Montréal
Design and implement large-scale deep learning models for domains such as computer vision and reinforcement learning. Improve data pipelines and apply deep learning methods to telemetry and time series forecasting data.
On-site · Montréal
Provide mission-critical support for proprietary trading applications, including software deployment, configuration, and system monitoring. Maintain and enhance internal scraping tools and provide technical support during trading operations to resolve critical issues.
On-site · Montréal
The Junior Strategy and Operations Analyst will focus on developing trading strategies to capture market-moving events and provide insights to traders. This involves analyzing market sentiment and refining existing practices.
On-site · Montréal
The specialist will deploy, maintain, and optimize GPU infrastructure for large-scale LLM inference workloads, architecting distributed serving solutions for multi-node, multi-GPU model deployments. Responsibilities also include managing GPU-enabled Kubernetes clusters, configuring network and storage solutions, and troubleshooting performance bottlenecks across the entire stack.
On-site · Montréal
The role involves designing and building data pipelines for RAG systems, including ingestion, chunking, embedding generation, and vector storage, while also building ingestion pipelines for structured and unstructured data into a centralized data lake. Responsibilities also include developing data processing workflows for model fine-tuning and inference, and building monitoring frameworks for retrieval quality and performance.
Remote · Montréal, Quebec, Canada
The role involves building internal systems that leverage AI and Machine Learning to create tooling for the firm. The developer will collaborate with various teams to define and implement critical features while ensuring system uptime and reliability.
On-site · Montréal
Design, develop, test, and deploy proprietary software solutions including MLOps, data pipelines, and full-stack applications. Collaborate with quantitative traders and researchers to solve complex problems using a data-driven approach.
On-site · Montréal
The Data Analyst will analyze non-financial post-event data to gain insights and discover potential issues. They will also collaborate with the development team to create analysis tools and develop scripts for data manipulation.
On-site · Montréal
You will design and operate agentic frameworks to process real-time market data and infrastructure telemetry. Additionally, you will be responsible for full-stack performance, ensuring high reliability and low latency in production trading systems.
On-site · Montréal
Design and implement large-scale deep learning models for computer vision, reinforcement learning, and time series forecasting. Collaborate with researchers and traders to solve complex AI/ML problems and improve data pipelines.
