Top Engineering Jobs

Run a live trading simulation: build and deploy a Python trading bot, convert logic into real-time trades, compete against other teams and IMC bots, apply research-driven thinking, and network with IMC traders. Bring a laptop and a problem-solving mindset. Food, refreshments, and prizes provided.

On-site coding competition where participants solve 20 rapid computer-science problems on IMC's platform, track progress on a live leaderboard, network with IMC technologists, and compete for prizes. Bring a laptop and a problem-solving mindset; event includes food and refreshments.

The Quantitative Developer will develop systems from research to production, build simulation infrastructure, manage feature pipelines, and troubleshoot issues in quantitative trading environments.

Engineer and operate large-scale bare-metal Linux infrastructure, build automation and provisioning workflows, develop Python/Bash tools, extend monitoring/telemetry, manage configuration at fleet scale, troubleshoot performance and networking, and collaborate with stakeholders to maintain reliability and efficiency.

Design and verify next-generation ASICs for latency-sensitive trading systems. Responsibilities include RTL development in SystemVerilog, verification and testing, debugging, integration, tooling and automation, and cross-team collaboration to meet performance and reliability goals.

Perform hands-on electronics lab work: validate and bring up circuit boards and ASICs, operate and maintain test equipment and fixtures, manage inventory and lab infrastructure, support manufacturing coordination, assembly, shipping, and documentation to enable hardware production and deployment.

Build, operate, and scale large-scale data storage platforms (Hadoop, S3-compatible, enterprise storage). Tune Linux for I/O performance, automate deployments with Ansible/Puppet, implement observability with Prometheus, and partner with engineers on storage- and Kafka-focused data solutions. Familiarity with Kubernetes and development in Java/Python required.

Design, implement, and deploy ML inference engines on custom FPGA/ASIC hardware. Perform HW/SW co-design with traders and researchers, optimize neural networks for low latency, and build quantization/compression tools to translate ML frameworks to RTL for rapid production deployment.

This role involves ensuring system continuity in trading operations, developing automation tools, and improving system performance in a trading environment.

Support researchers and ML engineers to optimize and scale HPC workloads on CPU/GPU infrastructure. Analyze performance, diagnose bottlenecks across storage, networking, and schedulers, implement profiling and benchmarking, influence platform design, and define best practices for shared compute environments while ensuring security and compliance.