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At IMC, technology is not a department; it’s at the heart of everything we do. Developed in house, our innovative software makes millions of trading decisions daily, and we win by making better and faster decisions than our competition. IMC’s Sydney-based Java teams work on a wide variety of applications, tools and functionalities, including trading algorithm implementations, option pricing, calculating volatility, simulation frameworks, market risk applications, trade reconciliation applications and data analysis & visualisation tools for traders. We frequently need to develop not just the business applications themselves, but also the tools that keep our development process at the cutting edge. This role sits within our Data Engineering team. The team builds highly-scalable, high-throughput, low-latency Java applications that move and transform data from thousands of sources at Petabyte scale powering everything from real-time trading to analytics.You’ll work on a mix of greenfield and re-engineering projects, collaborating with developers globally to build scalable, reliable data platforms. Balancing speed with quality, you’ll write robust, testable software and make thoughtful trade-offs between latency, throughput, simplicity and maintainability. Your core responsibilities include: Design, build, test and deploy high-performance Java systems for real-time and batch data processing. Develop tools and services around Kafka, Avro, Parquet and related streaming technologies. Contribute to internal frameworks for querying, storage, and data transformation — used globally across IMC. Partner with traders, researchers, and engineers to define requirements and deliver scalable data solutions. Own projects end-to-end, from requirements and architecture through to production deployment and monitoring. Continuously assess and introduce emerging technologies to improve performance, maintainability, and developer productivity.. Your Skills and Experience: 5+ years of experience as a Software Engineer with Java Experience in the latest versions of Java is highly desirable Proven experience building scalable, low-latency, high-throughput applications. Familiarity with Kafka, Avro, Parquet and other data-oriented technologies is highly desirable. Experience with Docker and Kubernetes, and confidence working in Linux environments. Strong analytical and troubleshooting skills, with the ability to solve complex technical challenges independently. Experience gathering business requirements and translating them into technical solutions. Curious, adaptable, and proactive; comfortable working in a fast-paced environment with minimal supervision. Our tech stack includes an ever-evolving range of systems and technologies, and our engineers have the freedom to choose the best solution for the problem at hand. If a new technology has the potential to add value, we’ll actively invest in exploring, adopting and developing it. #LI-DNI 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.

IMC is building a new Power and Gas Trading business in Aarhus, Denmark, the hub for power and gas trading in Europe. Backed by one of the world’s most successful trading firms, this new venture combines the energy and autonomy of a startup with the global reach, stability, and expertise of IMC’s 30+ years in trading. We are building a strong, independent Aarhus-based team with local leadership, supported by IMC’s world-class technology, quantitative research, and trading infrastructure. To achieve our ambitious hiring goals, we are seeking strong Software Engineers to join the team and play a pivotal role in helping us grow this new business. Your Core Responsibilities: Build, as part of a team, a full technology stack that supports power and gas trading, including exchange connectivity, trading systems, trading strategies, data analysis, and pricing. We are looking for strong developers that specialised in back-end, algorithms, trading systems, execution systems or other relevant domains Maintain and improve the tech stack in collaboration with trading Train new joiners Your Skills and Experience: Strong academic background, preferably in computer science or a quantitative field 2+ years of professional experience as a software engineer Experience European power and gas trading industry is a plus Strong programming skills in Java. Experience with other relevant programming languages such as Python or C++ is considered a plus Excitement for working in a start-up environment and a variety of systems/platforms/tools The ability able to work on greenfield projects under minimal supervision and to take full ownership of the applications you build A high degree of flexibility and adaptability: willing and able to deal with uncertainty and ambiguity in a rapidly evolving environment Fluency in English 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.

As a Machine Learning Engineer, you will play a pivotal role in building systems that drive the training and deployment of large-scale ML models across our global operations. You'll collaborate with leading researchers, hardware experts, and software engineers to build robust solutions that maximize the potential of GPU acceleration, distributed computing, and the latest open-source tools. Your work will influence our trading strategies by accelerating experimentation cycles that foster continuous innovation and refinement. This is a unique opportunity to solve problems at the intersection of advanced machine learning and trading, where your contributions will shape the future of IMC’s technology and trading capabilities. Your Core Responsibilities: The opportunity to be in a brand new position in a growing team Develop large-scale distributed training pipelines to manage datasets and complex models Build and optimize low-latency inference pipelines, ensuring models deliver real-time predictions in production systems Develop libraries to improve the performance of machine learning frameworks Maximize performance in training and inference using GPU hardware and acceleration libraries Design scalable model frameworks capable of handling high-volume trading data and delivering real-time, high-accuracy predictions Collaborate with quantitative researchers to automate ML experiments, hyperparameter tuning, and model retraining Partner with HPC specialists to optimize workflows, improve training speed, and reduce costs Evaluate and roll out third-party tools to enhance model development, training, and inference capabilities Dig into the internals of open-source ML tools to extend their capabilities and improve performance Your Skills and Experience: 5+ years of experience in machine learning with a focus on training or inference systems Hands-on experience with real-time, low-latency ML pipelines in high-performance environments is a strong plus Strong engineering skills, including Python, CUDA, or C++ Knowledge of machine learning frameworks such as PyTorch, TensorFlow, or JAX Proficiency in GPU programming for training and inference acceleration (e.g., CuDNN, TensorRT) Experience with distributed training for scaling ML workloads (e.g., Horovod, NCCL) Exposure to cloud platforms and orchestration tools A track record of contributing to open-source projects in machine learning, data science, or distributed systems 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.

As a Machine Learning Engineer, you will play a pivotal role in building systems that drive the training and deployment of large-scale ML models across our global operations. You'll collaborate with leading researchers, hardware experts, and software engineers to build robust solutions that maximize the potential of GPU acceleration, distributed computing, and the latest open-source tools. Your work will influence our trading strategies by accelerating experimentation cycles that foster continuous innovation and refinement. This is a unique opportunity to solve problems at the intersection of advanced machine learning and trading, where your contributions will shape the future of IMC’s technology and trading capabilities. Your Core Responsibilities: The opportunity to be in a brand new position in a growing team Develop large-scale distributed training pipelines to manage datasets and complex models Build and optimize low-latency inference pipelines, ensuring models deliver real-time predictions in production systems Develop libraries to improve the performance of machine learning frameworks Maximize performance in training and inference using GPU hardware and acceleration libraries Design scalable model frameworks capable of handling high-volume trading data and delivering real-time, high-accuracy predictions Collaborate with quantitative researchers to automate ML experiments, hyperparameter tuning, and model retraining Partner with HPC specialists to optimize workflows, improve training speed, and reduce costs Evaluate and roll out third-party tools to enhance model development, training, and inference capabilities Dig into the internals of open-source ML tools to extend their capabilities and improve performance Your Skills and Experience: 5+ years of experience in machine learning with a focus on training or inference systems Hands-on experience with real-time, low-latency ML pipelines in high-performance environments is a strong plus Strong engineering skills, including Python, CUDA, or C++ Knowledge of machine learning frameworks such as PyTorch, TensorFlow, or JAX Proficiency in GPU programming for training and inference acceleration (e.g., CuDNN, TensorRT) Experience with distributed training for scaling ML workloads (e.g., Horovod, NCCL) Exposure to cloud platforms and orchestration tools A track record of contributing to open-source projects in machine learning, data science, or distributed systems 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.

As a Machine Learning Engineer, you will play a pivotal role in building systems that drive the training and deployment of large-scale ML models across our global operations. You'll collaborate with leading researchers, hardware experts, and software engineers to build robust solutions that maximize the potential of GPU acceleration, distributed computing, and the latest open-source tools. Your work will influence our trading strategies by accelerating experimentation cycles that foster continuous innovation and refinement. This is a unique opportunity to solve problems at the intersection of advanced machine learning and trading, where your contributions will shape the future of IMC’s technology and trading capabilities. Your Core Responsibilities: Develop large-scale distributed training pipelines to manage datasets and complex models Build and optimize low-latency inference pipelines, ensuring models deliver real-time predictions in production systems Develop libraries to improve the performance of machine learning frameworks Maximize performance in training and inference using GPU hardware and acceleration libraries Design scalable model frameworks capable of handling high-volume trading data and delivering real-time, high-accuracy predictions Collaborate with quantitative researchers to automate ML experiments, hyperparameter tuning, and model retraining Partner with HPC specialists to optimize workflows, improve training speed, and reduce costs Evaluate and roll out third-party tools to enhance model development, training, and inference capabilities Dig into the internals of open-source ML tools to extend their capabilities and improve performance Your Skills and Experience: 3+ years of experience in machine learning with a focus on training or inference systems Hands-on experience with real-time, low-latency ML pipelines in high-performance environments is a strong plus Strong engineering skills, including Python, CUDA, or C++ Knowledge of machine learning frameworks such as PyTorch, TensorFlow, or JAX Proficiency in GPU programming for training and inference acceleration (e.g., CuDNN, TensorRT) Experience with distributed training for scaling ML workloads (e.g., Horovod, NCCL) Exposure to cloud platforms and orchestration tools A track record of contributing to open-source projects in machine learning, data science, or distributed systems 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.

As a Machine Learning Engineer, you will play a pivotal role in building systems that drive the training and deployment of large-scale ML models across our global operations. You'll collaborate with leading researchers, hardware experts, and software engineers to build robust solutions that maximize the potential of GPU acceleration, distributed computing, and the latest open-source tools. Your work will influence our trading strategies by accelerating experimentation cycles that foster continuous innovation and refinement. This is a unique opportunity to solve problems at the intersection of advanced machine learning and trading, where your contributions will shape the future of IMC’s technology and trading capabilities. Your Core Responsibilities: Develop large-scale distributed training pipelines to manage datasets and complex models Build and optimize low-latency inference pipelines, ensuring models deliver real-time predictions in production systems Develop libraries to improve the performance of machine learning frameworks Maximize performance in training and inference using GPU hardware and acceleration libraries Design scalable model frameworks capable of handling high-volume trading data and delivering real-time, high-accuracy predictions Collaborate with quantitative researchers to automate ML experiments, hyperparameter tuning, and model retraining Partner with HPC specialists to optimize workflows, improve training speed, and reduce costs Evaluate and roll out third-party tools to enhance model development, training, and inference capabilities Dig into the internals of open-source ML tools to extend their capabilities and improve performance Your Skills and Experience: 3+ years of experience in machine learning with a focus on training or inference systems Hands-on experience with real-time, low-latency ML pipelines in high-performance environments is a strong plus Strong engineering skills, including Python, CUDA, or C++ Knowledge of machine learning frameworks such as PyTorch, TensorFlow, or JAX Proficiency in GPU programming for training and inference acceleration (e.g., CuDNN, TensorRT) Experience with distributed training for scaling ML workloads (e.g., Horovod, NCCL) Exposure to cloud platforms and orchestration tools A track record of contributing to open-source projects in machine learning, data science, or distributed systems 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.

IMC Trading is seeking quantitative researchers with a proven track record to apply state-of-the-art machine learning & deep learning to solve challenging trading problems. This role is part of a central ML research team that collaborates across trading teams at IMC. The ideal candidate will have experience working with other researchers and engineers to build and continuously improve models, systems, and research tooling. We firmly believe that success for research-driven efforts lies in bringing together skills in ML, statistics, and trading intuition as well as a problem-solving mindset and pragmatism. This is an opportunity to dive deep into feature engineering and alpha research, and focus on applying a wide range of ML models as well as to perform research on building custom models. Your Core Responsibilities: Design and deploy machine learning models to enhance trading performance across various asset classes Research, test and prototype new algorithmic ideas; deploy advanced ML techniques applicable to market prediction, signal generation, and portfolio optimization Collaborate with quantitative traders, researchers, and developers to translate market insights into data-driven features and models Manage data acquisition, preprocessing, and feature engineering for structured and unstructured data sources Your Skills and Experience: PhD or Master’s in Engineering, Math, Statistics, Computer Science, or related quantitative field 2+ years of experience building applied ML models; previous experience in trading environment preferred Proven expertise in developing and deploying predictive models Strong programming skills in Python; proficiency in ML libraries such as PyTorch, TensorFlow, and/or high-performance libraries like Jax Strong understanding of theoretical foundations of state-of-the-art ML models Strong publication track record at ICML, ICLR, NeurIPS, or equivalent Ability and desire to work in a collaborative team environment Excellent written and verbal communication skills 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 $250,000 — $300,000 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.

IMC Trading is seeking quantitative researchers with a proven track record to apply state-of-the-art machine learning & deep learning to solve challenging trading problems. This role is part of a central ML research team that collaborates across trading teams at IMC. The ideal candidate will have experience working with other researchers and engineers to build and continuously improve models, systems, and research tooling. We firmly believe that success for research-driven efforts lies in bringing together skills in ML, statistics, and trading intuition as well as a problem-solving mindset and pragmatism. This is an opportunity to dive deep into feature engineering and alpha research, and focus on applying a wide range of ML models as well as to perform research on building custom models. Your Core Responsibilities: Design and deploy machine learning models to enhance trading performance across various asset classes Research, test and prototype new algorithmic ideas; deploy advanced ML techniques applicable to market prediction, signal generation, and portfolio optimization Collaborate with quantitative traders, researchers, and developers to translate market insights into data-driven features and models Manage data acquisition, preprocessing, and feature engineering for structured and unstructured data sources Your Skills and Experience: PhD or Master’s in Engineering, Math, Statistics, Computer Science, or related quantitative field 2+ years of experience building applied ML models; previous experience in trading environment preferred Proven expertise in developing and deploying predictive models Strong programming skills in Python; proficiency in ML libraries such as PyTorch, TensorFlow, and/or high-performance libraries like Jax Strong understanding of theoretical foundations of state-of-the-art ML models Strong publication track record at ICML, ICLR, NeurIPS, or equivalent Ability and desire to work in a collaborative team environment Excellent written and verbal communication skills 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 $250,000 — $300,000 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.