Jobs at IMC Trading

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.

Ten-week machine learning engineering internship focused on building systems for training and deploying large-scale ML models. Interns collaborate with researchers, hardware experts, and software engineers on GPU acceleration, distributed computing, and open-source tools supporting trading strategies. The program includes technical training, mentorship, professional development, financial markets education, and team activities. Successful interns may receive an opportunity for a graduate position.

Supports middle-office trade operations by reconciling trades, settlements, P&L, invoices, accounts, balances, and margin requirements. Investigates and resolves trade breaks, coordinates with trading, IT, clearing firms, and risk teams, and supports onboarding of exchanges and platforms. The role also manages datasets, produces reports, identifies automation opportunities, and contributes to operational improvements in a fast-paced financial markets environment.

Conduct ML and deep learning research to build, test, and deploy predictive models for trading. Collaborate with traders, researchers, and engineers to engineer features, preprocess data, prototype algorithms, and improve production research tooling to enhance trading performance.

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.

Provides in-house corporate legal support for an international proprietary trading organization. Responsibilities include advising on corporate law, entity structures, intracompany transactions, tax matters, and organizational actions; drafting and negotiating agreements; preparing legal memoranda; and supporting contracts, regulatory safeguards, and cross-functional business objectives.

Conduct research on low-latency machine learning inference and hardware acceleration. Architect and implement an ML research project, collaborate with hardware engineers, evaluate neural architecture search and quantization methods, and deploy solutions on FPGAs or custom ASICs. Present findings and deliver a prototype or benchmark while assessing performance, engineering costs, and industry impact.

Own global strategic sourcing for storage infrastructure and SaaS categories, including vendor strategy, renewals, license optimization, consolidation, negotiations, consumption-based spend governance, and supplier relationships. Partner with engineering, infrastructure, security, and finance teams on storage and software investments. Lead vendor evaluations, monitor market trends, mitigate risk, and coach sourcing teams.

Own global hardware sourcing strategy across GPUs, servers, networking, storage, and enterprise equipment. Manage executive relationships with strategic vendors representing $300M-$500M+ in annual spend, negotiate complex supply agreements, secure constrained GPU and component allocations, optimize costs and total cost of ownership, and mitigate supply-chain risks. Partner with engineering, finance, and capacity planning leaders on infrastructure roadmaps and investment decisions while coaching sourcing teams globally.

Conduct quantitative research to design, implement, and deploy mathematical trading models. Build custom tools for exploratory analysis, apply rigorous quantitative techniques to solve complex problems, and collaborate with traders and developers to productionize models while maintaining best practices.

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.

Interest form for students who want to learn more about the 2027 US Chess Academy. Applicants join a prospect list and may receive information about upcoming opportunities, program updates, and how to play.

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.

As a Software Engineer, you will build AI systems to enhance developer workflows, implementing agents and servers, and ensuring code reliability through evaluation pipelines.

Design, build, and operate big-data and streaming platforms (Kafka, Hadoop, Dremio). Develop, deploy, and monitor data pipelines using Java, Python, Spark/Flink; collaborate on data modeling and ingestion, ensure data integrity and availability, act as a Big Data SME, and perform root-cause analysis.