Software Developer (Research)

DRW is a diversified trading company with over 30 years of experience that brings together sophisticated technology and exceptional people to operate across global markets. We value autonomy and the ability to pivot quickly to seize opportunities, which is why we operate using our own capital and trade at our own risk.

Based in Chicago and with offices in the U.S., Canada, Europe, and Asia, we trade various asset categories, including fixed-income securities, FNBs, equities, currencies, commodities, and energy on major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital, and crypto-assets.

We operate with respect, curiosity, and an open mind. People who thrive here share our belief that it's not just what we do that matters — it's how we do it. DRW is a place of high expectations, integrity, innovation, and a willingness to challenge the consensus.

We build systems that transform real-world events into exploitable signals, with low latency and high reliability, in a trading environment where being right a second too late is as bad as being wrong. This role sits at the intersection of research and infrastructure: you will formulate hypotheses, validate them with rapid analyses, and then build production systems that leverage them.

We also integrate LLMs as a first-class component of the toolchain, not as an ancillary experiment. People who succeed here wield an agentic harness as naturally as a profiler, and know precisely where each one remains reliable.

How You'll Make an Impact

Discovery and Research

• Expand our event-driven strategy to equity flows, market news, social media, and infrastructure telemetry.
• Launch rapid analyses in Python/Jupyter to assess signal quality, and turn your discoveries into system improvements.

LLM and Agent-Driven Systems

• Design and operate agent frameworks — tools, context management, evaluations, guardrails — that actually work on our data and infrastructure, and take ownership of their quality in production.
• Apply LLMs where they provide a real advantage (extraction, classification, triage, search acceleration) and decide not to use them when they're not appropriate.

Infrastructure and Technical Leadership

• Be accountable for full-stack performance, from edge network to in-memory stores — instrument, monitor, and debug production systems alongside operations, while maintaining very tight SLOs (service level objectives).
• Lead greenfield initiatives (new projects), design reviews, and post-mortems.

Core Skills

• 3–5 years of experience in designing real-time or data-intensive systems (we favor trajectory and depth over the exact number of years).
• Deep understanding of LLMs, not just their usage — comprehension of the real behavior of these models (context and failure modes, tool use, structured outputs, cost/latency trade-offs, hallucination mitigation) and ability to build the framework around a model: tools, memory, retries, evaluations, boundaries of « human-in-the-loop ». Present a concrete project you've deployed and can explain end-to-end, including what broke.
• Strong fundamentals in engineering in Python, Go, or Rust. Preference, not exclusion — deep systems experience in another serious language is transferable.
• Deep knowledge of network programming and protocols — TCP/UDP/IP, DNS, BGP, HTTP(S), WebSocket, QUIC.
• Ability to quickly turn POCs (proof of concept) into production — validate statistical significance, iterate fast, deliver, and explain results to both technical and non-technical audiences.
• Bachelor's or master's degree in computer science, data science, mathematics, or related field.
• Who Thrives Here

This is a high-stakes, competitive environment; we seek people who want it rather than tolerate it. You'll likely recognize yourself if:

• You want really hard and measurable problems — where the scoreboard is real and public within the team.
• You go fast without rushing, and prefer to deliver, measure, and correct rather than dither indefinitely.
• You're comfortable getting it wrong quickly and in public, and updating your position rather than defending it.

Bonus Qualifications

• Expertise in the current LLM ecosystem — agent frameworks, MCP, RAG architectures, evaluation tools, or local/self-hosted inference.
• Demonstrated success in reducing latency on NGINX, Envoy, or custom load-balancing layers.
• Experience in high-pressure domains — trading floors, esports, competitive sports, or hackathons.
• Open-source contributions, technical blogging, or conference presentations.

What DRW Montreal Has to Offer

• Recognized as one of Canada's top employers for 8 years
• Commitment to continuous learning and development
• A cutting-edge benefits and perks package
• Employee well-being and work-life balance initiatives
• Community initiatives, volunteer programs, and opportunities to give back
• Discover all our benefits at: https://drw.com/en/work-at-drw/benefits-montreal

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