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We are seeking a driven Java engineer to join our global research platform team in Mumbai. The team builds and operates the compute and data platform that powers all of IMC's quantitative research: a large-scale Kubernetes-based research cluster, a distributed job scheduling platform used by every trading and research team, and the market-data and dataset services that feed research on it. Mumbai runs one of the platform's regional production deployments, and you'll collaborate closely with platform colleagues in Amsterdam, Chicago and Sydney. Your Core Responsibilities: Design, build and operate the Java backend of our distributed job scheduling platform: the job controller and state machine, scheduling integrations, resource and cost tracking, and the failure-recovery machinery that keeps research workloads running at scale Develop gRPC/protobuf APIs consumed by Python, Java and C++ clients across the firm Build event-driven services on Kafka for job lifecycle tracking, data lineage, and dataset orchestration Work hands-on with Kubernetes at scale: pod scheduling, fair-share queueing, preemption and multi-cluster placement Instrument, monitor and firefight production systems, and drive root-cause analysis of performance bottlenecks Support and consult research users in the India office Your Skills and Experience: 3+ years of professional Java development experience (Java 17+, Maven/Gradle, strong grasp of concurrency and JVM performance) 2+ year of hands-on experience with Kubernetes and Docker (building on the K8s API is a strong plus) Comfortable developing in Python; our client libraries and research users are Python-first, and you'll work on both sides of the API Solid understanding of distributed systems fundamentals: state machines, retries/idempotency, event-driven architectures, consistency trade-offs Experience with workload scheduling or batch/compute orchestration systems (e.g. Kubernetes schedulers, Slurm, YARN, Kueue, Ray, Airflow) Experience with messaging/streaming systems such as Kafka Working knowledge of NoSQL and time-series/SQL databases (e.g. MongoDB, PostgreSQL) Experience with gRPC/protobuf or similar RPC frameworks is a plus Strong Linux fundamentals and scripting (bash, Python) Experience with monitoring stacks (Prometheus, Grafana, alerting) and comfort operating what you build Demonstrated ability to troubleshoot across the stack from application code through Kubernetes to network and storage Exposure to object storage (S3) or high-performance data formats (Parquet, Iceberg) About Us IMC is a research-driven trading firm where quantitative modeling, machine learning, and engineering shape how modern markets are traded. A stabilizing force in markets since 1989, we provide liquidity across trading venues, delivering the best outcome in value and risk management to investors. Using our own technology and capital, we build proprietary systems and algorithms that operate across global markets. Our researchers, traders, and engineers work as a collective, combining rapid experimentation, advanced infrastructure, and real-time feedback to turn insight into execution and execution into advantage.

The Machine Learning Frameworks team exists for two reasons: making the research iteration loop as fast and frictionless as possible, and making production run as fast as the hardware allows. Both matter, and figuring out how to do both at once is most of what makes the work fun. Concretely, we build optimisers, code generators, runtime libraries, and the orchestration layer that runs computation across heterogeneous hardware. The stack spans C++, Rust, Python, MLIR, and CUDA. You don't need to know all of these things but should want to work at this level of the stack. The work is broad. Some of it is high-level, looking at the whole compute pipeline, orchestrating the system and creating a cohesive product. Some of it is in the details, getting into hardware behaviour, dissecting compute graphs, squeezing the last bit of performance out of the hot path. Our job is managing the whole stack, top to bottom. About you You write production code in a systems language. C++ or Rust, or something close enough that picking them up isn't the hard part. The right tool matters more to you than your favourite one You like understanding what a language compiles down to and how it runs on hardware. You're comfortable being handed an unfamiliar part of the stack and working it out. You like working with stakeholders and you’re good at figuring out what someone actually needs, not just what they asked for You've done this commercially. You've owned something in production that other people relied on. Not necessarily big, but something you had to maintain, debug and live with long after you shipped it. What you don't need A finance background. Exposure to every language we touch. We hire engineers who like to solve the problems our traders face - we'll teach you the context on the ground About Us IMC is a research-driven trading firm where quantitative modeling, machine learning, and engineering shape how modern markets are traded. A stabilizing force in markets since 1989, we provide liquidity across trading venues, delivering the best outcome in value and risk management to investors. Using our own technology and capital, we build proprietary systems and algorithms that operate across global markets. Our researchers, traders, and engineers work as a collective, combining rapid experimentation, advanced infrastructure, and real-time feedback to turn insight into execution and execution into advantage.

The Research Engineering team develops and deploys the pipelines connecting a research idea all the way to its rollout in production. We exist to ensure that the entire pipeline describing our research is efficient, effective, and scalable. People in our team are avid collaborators and work in tight feedback loops with our researchers. We talk through problems on desk, prepare solutions same day, and work out how to deploy safely for tomorrow. The scope of the team covers anything that accelerates the path from research to production at massive scale. This could be designing our external data ingestion pipelines, writing our feature discovery and storage systems, building our model validators and experiment trackers, authoring and deploying a bespoke algorithm, or figuring out how to roll out something novel. We use a broad toolkit including Python, C++ and internal domain-specific languages, and are happy to pick up new tools and languages as required. About you You write production code in both Python and C++. You reach for the second one when it matters, and you know when it does. You're naturally curious about how other teams' systems work, not just your own, and you often end up being the person who spots where things won't fit together before it becomes a problem. You enjoy working on many projects at once, seeing connections and opportunities between them which others miss. You’re motivated to solve issues with whatever tool is best, rather than a preference towards deep specialisation in one area. You like working with research stakeholders across the business and you're good at figuring out what someone actually needs, not just what they asked for. You've done this commercially. You've owned something in production that other people relied on. Not necessarily big, but something you had to maintain, debug and live with long after you shipped it What you don’t need A finance background. Every language we touch. A particular set of years in any particular role. We hire engineers who like to solve the problems our traders face - we'll teach you the context on the ground. About Us IMC is a research-driven trading firm where quantitative modeling, machine learning, and engineering shape how modern markets are traded. A stabilizing force in markets since 1989, we provide liquidity across trading venues, delivering the best outcome in value and risk management to investors. Using our own technology and capital, we build proprietary systems and algorithms that operate across global markets. Our researchers, traders, and engineers work as a collective, combining rapid experimentation, advanced infrastructure, and real-time feedback to turn insight into execution and execution into advantage.

The Research Engineering team develops and deploys the pipelines connecting a research idea all the way to its rollout in production. We exist to ensure that the entire pipeline describing our research is efficient, effective, and scalable. People in our team are avid collaborators and work in tight feedback loops with our researchers. We talk through problems on desk, prepare solutions same day, and work out how to deploy safely for tomorrow. The scope of the team covers anything that accelerates the path from research to production at massive scale. This could be designing our external data ingestion pipelines, writing our feature discovery and storage systems, building our model validators and experiment trackers, authoring and deploying a bespoke algorithm, or figuring out how to roll out something novel. We use a broad toolkit including Python, C++ and internal domain-specific languages, and are happy to pick up new tools and languages as required. About you You write production code in both Python and C++. You reach for the second one when it matters, and you know when it does. You're naturally curious about how other teams' systems work, not just your own, and you often end up being the person who spots where things won't fit together before it becomes a problem. You enjoy working on many projects at once, seeing connections and opportunities between them which others miss. You’re motivated to solve issues with whatever tool is best, rather than a preference towards deep specialisation in one area. You like working with research stakeholders across the business and you're good at figuring out what someone actually needs, not just what they asked for. You've done this commercially. You've owned something in production that other people relied on. Not necessarily big, but something you had to maintain, debug and live with long after you shipped it What you don’t need A finance background. Every language we touch. We hire engineers who like to solve the problems our traders face - we'll teach you the context on the ground. About Us IMC is a research-driven trading firm where quantitative modeling, machine learning, and engineering shape how modern markets are traded. A stabilizing force in markets since 1989, we provide liquidity across trading venues, delivering the best outcome in value and risk management to investors. Using our own technology and capital, we build proprietary systems and algorithms that operate across global markets. Our researchers, traders, and engineers work as a collective, combining rapid experimentation, advanced infrastructure, and real-time feedback to turn insight into execution and execution into advantage.

We are seeking a Software Engineer to help build the technology and analytical frameworks used to understand, measure, and optimize risk across the firm's trading businesses. Working directly with Risk Managers and software engineers globally, you will develop systems that help the firm analyze exposures, scenarios, capital, liquidity, and other risk factors across all asset classes. You will have significant autonomy to improve existing platforms, build new tools, and pursue opportunities that make the risk organization more effective. This role is ideal for someone who enjoys combining software engineering, data science, and financial markets to solve complex, high-impact problems. Your Core Responsibilities: Design and build analytical tools that help Risk Managers understand portfolio exposures, stress scenarios, capital usage, and emerging risks Build high-end dashboards and visualization tools for stakeholders globally. Work with large data sets, data pipelines that support storage, retrieval, and analysis across the risk organization. Partner directly with Risk Managers to identify opportunities and rapidly translate ideas into production systems while collaborating within the firm's global risk development organization. Collaborate with engineering, trading, quantitative research, operations, and data teams across the firm Take ownership of projects from concept through production deployment Your Skills and Experience: 3–5+ years of professional software engineering experience Strong development skills in Java and/or Python Experience building and supporting production systems Interest in financial markets, risk management, data science, and quantitative analysis Strong analytical and problem-solving skills Self-starter with a high degree of ownership and initiative Distributed systems and service-oriented architectures Kubernetes and containerized applications React and modern web development PostgreSQL, ClickHouse, and analytical databases Parquet, Hadoop, and large-scale data platforms Data pipelines, ETL frameworks, and APIs The Base Salary range for the role is included below. Base salary is only one component of total compensation; all full-time, permanent positions are eligible for a discretionary bonus and benefits, including paid leave and insurance. Please visit Benefits - US | IMC Trading for more comprehensive information. Salary Range $175,000 — $225,000 USD About Us IMC is a research-driven trading firm where quantitative modeling, machine learning, and engineering shape how modern markets are traded. A stabilizing force in markets since 1989, we provide liquidity across trading venues, delivering the best outcome in value and risk management to investors. Using our own technology and capital, we build proprietary systems and algorithms that operate across global markets. Our researchers, traders, and engineers work as a collective, combining rapid experimentation, advanced infrastructure, and real-time feedback to turn insight into execution and execution into advantage.

The Live Trading, Analysis & Tooling engineering team exists to make sure our traders and researchers have all the tools they need to run and analyse their trading at scale. We tackle both ends of scaling - we help traders maximise how many strategies they can trade, and help them analyse specific moments to find new opportunities. Our team sits close to the people who use what we build, with short iteration loops, fast feedback, and a lot of conversation. The work is broad. We build tools that help traders orchestrate strategies across our full product range. We build infrastructure that makes large amounts of data quickly explorable. We model risk, analyse trades, and figure out where new opportunities might be. Our toolkit is just as broad. Python, Java, React, SQL, any tool that solves the issue at hand. About you You're energised by problems where the brief doesn't exist yet. Working out what to build is as much the job as building it You can move between languages without it slowing you down. The right tool matters more to you than your favourite one You like working with stakeholders across the business and you're good at figuring out what someone actually needs, not just what they asked for You can pivot. You enjoy trying out new ideas quickly and scaling them once they’ve proven value - or throwing them out if they didn’t work What you don't need A finance background. Experience in any particular language. A specific set of years in any particular role. We hire engineers who like to solve the problems our traders face - we'll teach you the context on the ground. About Us IMC is a research-driven trading firm where quantitative modeling, machine learning, and engineering shape how modern markets are traded. A stabilizing force in markets since 1989, we provide liquidity across trading venues, delivering the best outcome in value and risk management to investors. Using our own technology and capital, we build proprietary systems and algorithms that operate across global markets. Our researchers, traders, and engineers work as a collective, combining rapid experimentation, advanced infrastructure, and real-time feedback to turn insight into execution and execution into advantage.

The Development Platform organization at IMC Trading is focused on accelerating tech team workflows by providing self-service tools, services, documentation, and support. We design, build, and maintain the platforms that IMC's software development lifecycle depends on, establishing a consistent technical foundation across regions and empowering teams to innovate efficiently. IMC is embedding agentic AI directly into the developer workflow for our production-critical systems. The Development Platform team operates the infrastructure that makes this possible: the environments where AI agents run, the integrations that connect them to our systems, and the safety and security controls that keep them reliable and auditable. We are seeking a versatile Systems Engineer to build and operate the infrastructure behind IMC's AI-powered engineering initiative. You will integrate AI SaaS offerings, run the containerization and virtualization layers that AI agents depend on, and harden the security of agents and the internal services they interact with. As AI adoption across our tech teams grows, so does the need for robust, secure, and observable infrastructure around it. Based in Sydney, you will be the local point of contact for our global AI platform and infrastructure teams, collaborating closely with them while supporting the development teams who consume these capabilities every day. Your Core Responsibilities: Integrate, deploy, and operate AI SaaS offerings and self-hosted AI services, collaborating cross-functionally to deliver new tools and capabilities to our tech teams. Design and maintain the containerization and virtualization environments in which AI agents, MCP servers, and supporting services run, ensuring they are isolated, reproducible, and scalable. Drive security hardening of AI agents and the internal services exposed to them: secrets management, access controls, sandboxing, network policy, and auditability of agent actions. Write and maintain code to extend, integrate, and automate the services we support, from API integrations to internal tooling and automation frameworks. Build the telemetry, monitoring, and evaluation infrastructure needed to make AI-driven workflows reliable, observable, and safe to run against production-critical systems. Partner with development teams to align platform capabilities with their evolving AI workflows, and act as the regional point of contact for global AI platform and infrastructure collaboration. Diagnose and resolve incidents swiftly, working with regional peers in a 'follow the sun' model to guarantee continuous system availability. Your Skills and Experience: 3+ years of work experience in a relevant role Bachelor's Degree in Computer Engineering, Computer Science or equivalent Strong programming experience in Python or Go; Shell scripting is a plus. Strong knowledge of Linux/Unix Systems Hands-on experience with containerization and virtualization technologies, including Kubernetes and Docker. Experience integrating and operating third-party SaaS solutions, both on-premises and leveraging AWS cloud services. Understanding of security principles and best practices, including secrets management, sandboxing, and compliance frameworks. Experience designing disaster recovery plans, high availability (HA) configurations, and failover strategies. Experience with CI/CD tools such as Jenkins, GitLab CI, or TeamCity, including the automation of build, test, and deployment processes. Curiosity and eagerness to learn about AI/LLM application patterns, even if you haven't worked closely with them yet; exposure to agentic AI tools and workflows (e.g., coding agents, MCP servers) or model-serving and evaluation infrastructure is a plus. About Us IMC is a research-driven trading firm where quantitative modeling, machine learning, and engineering shape how modern markets are traded. A stabilizing force in markets since 1989, we provide liquidity across trading venues, delivering the best outcome in value and risk management to investors. Using our own technology and capital, we build proprietary systems and algorithms that operate across global markets. Our researchers, traders, and engineers work as a collective, combining rapid experimentation, advanced infrastructure, and real-time feedback to turn insight into execution and execution into advantage.