Top Engineering Jobs in Chicago, IL

Operate and improve global developer platform infrastructure supporting source control, CI/CD, artifact repositories, build systems, observability, and AI services. Responsibilities include reliability and performance optimization, high availability, disaster recovery, incident response, capacity planning, automation, on-call practices, cloud SaaS integration, and collaboration with global development teams. The role requires hands-on Linux, programming, Kubernetes, Docker, CI/CD, security, and infrastructure operations experience.

Designs, manages, and optimizes on-premises Kubernetes clusters and containerized applications. Responsibilities include CI/CD implementation, security configuration, infrastructure automation, storage and networking management, troubleshooting, upgrades, backups, and disaster recovery. The role collaborates with internal technology teams to provide reliable, scalable, and self-service platform capabilities.

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.

Develop and maintain trading platform software and trading algorithms, identify technical opportunities, solve complex problems, and collaborate with traders, quantitative researchers, and engineers. The role involves working across the software development lifecycle, learning new technologies, and applying strong algorithmic and analytical skills in a dynamic financial markets environment.

Develop and automate verification solutions for complex hardware systems. Collaborate with RTL and software teams, create system- and block-level testbenches, use UVM and EDA tools, automate regression testing, and track coverage metrics through verification closure in a Linux environment.

Develop and maintain backend systems, automation, databases, data pipelines, dashboards, and visualization tools supporting finance, trading, and operations teams. Improve processing efficiency, system performance, and data accessibility across a global business intelligence environment. Collaborate with BI developers and business stakeholders while working with large datasets. The role requires Python, SQL, cloud, containerization, CI/CD, and agentic coding tool experience.

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.

Performance Engineer Interns conduct quantitative research on exchange and network technologies, design optimization strategies for electronic trading, develop AI agents, ETL pipelines, and Python algorithms, and reverse-engineer and stress-test low-latency systems. They collaborate with traders and hardware and software engineers to improve liquidity-taking, quoting, and ultra-low-latency trading strategies.

Conduct quantitative research on exchange technology and large datasets, design strategies for ultra-low-latency trading, and develop AI agents, ETL pipelines, and Python algorithms. Reverse-engineer and stress-test network and systems technologies, collaborating with traders and hardware and software engineers to optimize liquidity-taking and quoting strategies.

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