Senior Software Engineer - Quant trading

This role is with one of Dex’s trusted Partner companies. We work closely with their teams to truly understand their culture, goals, and what they’re looking for, so we can match you with the right opportunity for your goals!

If you’re interested, apply here to head to the website, where you can sign up and speak to Dex. After your call, you'll be sent the full match details. We’ll help manage your applications, and find other great matches to work you'll love.

Dex is partnering with some of the most prestigious quantitative trading firms in the world.

These firms are building bleeding-edge machine learning systems and high-performance infrastructure to trade billions of dollars daily across global markets and asset classes.

What You’ll Work On:

Develop scalable, elegant systems to ingest, store, and process petabytes of market and alternative data, ensuring cleanliness, consistency, and accessibility for research and modelling.

Design and implement high-performance, low-latency trading infrastructure, including order management, market connectivity, and simulation frameworks.

Deploy and integrate ML models into production, ensuring they operate in real-time and under tight latency constraints.

Optimise systems for performance and efficiency across networking, I/O, and compute layers.

Build observability into everything: robust monitoring, alerting, and telemetry for real-time insights into data pipelines, trading activity, and model behaviour.

Collaborate with researchers, quant developers, and infrastructure teams to bring strategies to life in production with rigour, reliability, and speed.

What you'll have

Strong programming skills in at least one of: C++, Python, Rust, or Java. C++ is commonly used for low-latency systems, and Python for data and ML workflows.

Experience with distributed systems, high-throughput messaging (e.g., Kafka, ZeroMQ, NATS), and real-time data processing.

Familiarity with modern data infrastructure: Databases (SQL and NoSQL), object stores, time-series databases, and streaming frameworks (e.g., Apache Flink, Spark Streaming).

Comfort working close to the metal: systems-level debugging, profiling, and performance tuning (CPU, memory, networking).

Bonus: experience with ML engineering, including model serving, feature stores, or integrating ML pipelines into live systems.

Bonus: Exposure to financial markets, pricing models, or trading systems is helpful but not required.

To be considered for this role and others like it, sign up to Dex, and the details of the role will be sent to you directly to confirm your application!

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