Careers at Imc

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: 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.

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.

IMC is looking for experienced quant researchers to develop high to mid frequency delta one trading strategies and predictive models for the APAC markets. If you’re excited about helping to push the boundaries of what we can do with Machine Learning in trading, unlocking the significant edges we have in execution, and collaborating to become the best trading firm worldwide, this may be the role for you. You will be responsible for performing large scale data analysis to derive statistically profitable predictions of market behaviour. These predictions are used to inform all of our trading, and improvements have a high and visible impact across the office. You will also help to shape the direction we take across research and tooling. We have longstanding and significant edges across market access, global reach, Options understanding and low latency. The rapid growth we’ve already seen in Machine Learning has unlocked these edges, and some of the most interesting and impactful problems are now being tackled. You will work as part of an established and growing research team, collaborating closely with traders, software and hardware developers to find improvements to our models and see them impact our production results. IMC competes and wins as a team, with open idea sharing and collaboration across disciplines, desks and offices. Your Core Responsibilities: Leverage deep learning techniques to improve prediction quality in a trading context Collaborate with feature engineers and traders, to help ensure the feature set is crafted and used to maximum effect Develop and improve sampling, weighting, cost, target, hyperparameters and network architecture to suit a range of problems and data presentations Push the team forward, by keeping abreast of the latest developments in industry and academia, and tackling some of the hardest problems we have in the quant space Mentor and grow the skills of more junior colleagues in the space, and clearly and simply explain complex concepts Apply understanding of distributed computing, and how to align training hardware and approach to rapidly achieve strong results on very large datasets Your Skills and Experience: Graduate & Postgraduate study from top universities, majoring in machine learning, statistics, or STEM subjects 3+ years experience as a quantitative modeller, with specific experience in the high to mid frequency delta one space. Have a proven track record of developing and improving deep learning models with proven outperformance in production Strong programming experience in at least one language, and mainstream deep learning framework (TensorFlow, PyTorch or other) Deep understanding of the strengths & weaknesses of CNN, RNN, LSTM and transformers 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 looking for experienced quant researchers to develop high to mid frequency delta one trading strategies and predictive models for the APAC markets. If you’re excited about helping to push the boundaries of what we can do with Machine Learning in trading, unlocking the significant edges we have in execution, and collaborating to become the best trading firm worldwide, this may be the role for you. You will be responsible for performing large scale data analysis to derive statistically profitable predictions of market behaviour. These predictions are used to inform all of our trading, and improvements have a high and visible impact across the office. You will also help to shape the direction we take across research and tooling. We have longstanding and significant edges across market access, global reach, Options understanding and low latency. The rapid growth we’ve already seen in Machine Learning has unlocked these edges, and some of the most interesting and impactful problems are now being tackled. You will work as part of an established and growing research team, collaborating closely with traders, software and hardware developers to find improvements to our models and see them impact our production results. IMC competes and wins as a team, with open idea sharing and collaboration across disciplines, desks and offices. Your Core Responsibilities: Leverage deep learning techniques to improve prediction quality in a trading context Collaborate with feature engineers and traders, to help ensure the feature set is crafted and used to maximum effect Develop and improve sampling, weighting, cost, target, hyperparameters and network architecture to suit a range of problems and data presentations Push the team forward, by keeping abreast of the latest developments in industry and academia, and tackling some of the hardest problems we have in the quant space Mentor and grow the skills of more junior colleagues in the space, and clearly and simply explain complex concepts Apply understanding of distributed computing, and how to align training hardware and approach to rapidly achieve strong results on very large datasets Your Skills and Experience: Graduate & Postgraduate study from top universities, majoring in machine learning, statistics, or STEM subjects 3+ years experience as a quantitative modeller, with specific experience in the high to mid frequency delta one space. Have a proven track record of developing and improving deep learning models with proven outperformance in production Strong programming experience in at least one language, and mainstream deep learning framework (TensorFlow, PyTorch or other) Deep understanding of the strengths & weaknesses of CNN, RNN, LSTM and transformers 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.

Our Machine Learning Internship is designed for curious, ambitious researchers who want to apply machine learning to complex, real-world problems. Over 10 weeks, you'll work alongside experienced researchers and mentors to develop models, analyze large-scale datasets, and contribute to research that informs IMC's trading strategies across global equities, futures, and options markets. You'll begin with a week of engaging, classroom-based learning in the proprietary trading landscape, then gain hands-on experience designing experiments, evaluating novel approaches, and tackling challenging problems in a collaborative, fast-paced environment where your work can have real-world impact. Split between our Amsterdam headquarters and time at our London office, the program also gives you the chance to broaden your network across IMC's regions. Throughout the program, you'll deepen your understanding of quantitative trading through a combination of classroom and on-desk training, while benefiting from professional development and networking opportunities. You'll receive comprehensive support from dedicated internship trainers and a one-on-one mentor to guide you in your work and professional development. We offer a highly competitive compensation package, including fully-furnished corporate accommodation and catered meals. High-performing interns may be considered for a full-time Graduate Researcher position upon graduation. Your Core Responsibilities: Conduct hands-on research to design, develop, and apply original machine learning algorithms, with the support to explore and innovate Analyze large-scale datasets, develop predictive models, and evaluate novel approaches to complex market problems Develop your research skills through hands-on project work, mentorship, and regular feedback from experienced researchers Enhance your understanding of quantitative trading through classroom-based instruction in options theory, market making, and related topics Your Skills and Experience: Currently in your penultimate year of study, graduating in 2028 A minimum of an MSc in Machine Learning, Statistics, Deep Learning, Probabilistic Programming, or a related quantitative field Strong foundations in statistics and machine learning, with a demonstrated research track record in ML, deep learning, or another quantitative field Proficiency in Python and core machine learning frameworks such as PyTorch Desirable: publications in respected journals covering deep learning or time-series modeling No prior finance knowledge or experience required Ability to start the internship on the last week of June 2027 You may submit one application per role each year. We strongly encourage you to focus on applying to a single role that best matches your skills and interests. Though you may apply to multiple roles, please note that each application will be evaluated based on the specific criteria established for that particular role. If you have already applied for this position during the current recruitment season and were not selected, you may reapply when the next recruitment season begins in August 2027. We encourage you to focus on enhancing your skillset before reapplying. Please note that IMC's internship program duration is less than 90 days, which unfortunately does not qualify for a Highly Skilled Migrant visa. Because of this and current regulations with the Immigratie en Naturalisatiedienst (IND), IMC is unable to obtain immigration sponsorship for candidates who currently have citizenship from Russia, Belarus or Iran, and attend university in one of the aforementioned countries. We greatly appreciate your understanding and hope to consider you for future opportunities. If you have citizenship from Ukraine, you will need to confirm that you currently hold a biometric passport so that IMC can obtain the correct immigration sponsorship for you. Please confirm by emailing CampusEU@imc.com . If you are currently residing or attending university outside of Russia, Belarus, or Iran, and have existing work authorisation in the Netherlands or are eligible to work without sponsorship, we encourage you to apply and inform our campus recruitment team of your situation: CampusEU@imc.com . 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.

Our Machine Learning Internship is designed for curious, ambitious researchers who want to apply machine learning to complex, real-world problems. Over 10–12 weeks, you'll work alongside experienced researchers and mentors to develop models, analyze large-scale datasets, and contribute to research that informs IMC's trading strategies across global equities, futures, and options markets. You'll gain hands-on experience designing experiments, evaluating novel approaches, and tackling challenging problems in a collaborative, fast-paced environment where your work can have real-world impact. Throughout the program, you'll deepen your understanding of quantitative trading through a combination of classroom and on desk training, while benefiting from professional development and networking opportunities. We offer a highly competitive compensation package, including travel and accommodation. High-performing interns may be considered for a full-time Graduate Researcher position upon graduation. YOUR CORE RESPONSIBILITIES: Conduct hands-on research to design, develop, and apply original machine learning algorithms, with the support to explore and innovate. Analyze large-scale datasets, develop predictive models, and evaluate novel approaches to complex market problems Develop your research skills through hands-on project work, mentorship, and regular feedback from experienced researchers Enhance your understanding of quantitative trading through classroom-based instruction in options theory, market making, and related topics YOUR SKILLS AND EXPERIENCE: Pursuing a PhD in Machine Learning, Computer Science, Electrical Engineering, Mathematics, Statistics, Physics, or a related quantitative field and graduating between September 2027 – July 2028 Strong foundations in machine learning, probability, and statistics, with experience applying advanced ML techniques to solve challenging research or real-world problems Demonstrated hands-on research experience in deep learning fundamentals such as neural network architectures, sequence modeling, training dynamics, or optimization Proficiency in Python and modern machine learning frameworks such as PyTorch, Tensorflow, and/or JAX Demonstrated research excellence through publications, preprints, research internships, or significant research projects; publications at venues such as NeurIPS, ICML, ICLR, or equivalent conferences are highly preferred Must be able to start internship in-person on June 7, 2027 You may submit one application per role each year. We strongly encourage you to focus on applying to a single role that best matches your skills and interests. Though you may apply to multiple roles, please note that each application will be evaluated based on the specific criteria established for that particular role. If you have already applied for this position during the current recruitment season and were not selected, you may reapply when the next recruitment season begins in 2027. 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. Base Salary: $300,000 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.

ROLE OVERVIEW Our Machine Learning Internship is designed for curious, ambitious researchers who want to apply machine learning to complex, real-world problems. Over 10–12 weeks, you'll work alongside experienced researchers and mentors to develop models, analyze large-scale datasets, and contribute to research that informs IMC's trading strategies across global equities, futures, and options markets. You'll gain hands-on experience designing experiments, evaluating novel approaches, and tackling challenging problems in a collaborative, fast-paced environment where your work can have real-world impact. Throughout the program, you'll deepen your understanding of quantitative trading through a combination of classroom and on desk training, while benefiting from professional development and networking opportunities. We offer a highly competitive compensation package, including travel and accommodation. High-performing interns may be considered for a full-time Graduate Researcher position upon graduation. YOUR CORE RESPONSIBILITIES: Conduct hands-on research to design, develop, and apply original machine learning algorithms, with the support to explore and innovate. Analyze large-scale datasets, develop predictive models, and evaluate novel approaches to complex market problems Develop your research skills through hands-on project work, mentorship, and regular feedback from experienced researchers Enhance your understanding of quantitative trading through classroom-based instruction in options theory, market making, and related topics YOUR SKILLS AND EXPERIENCE: Pursuing a PhD in Machine Learning, Computer Science, Electrical Engineering, Mathematics, Statistics, Physics, or a related quantitative field Strong foundations in machine learning, probability, and statistics, with experience applying advanced ML techniques to solve challenging research or real-world problems Demonstrated hands-on research experience in deep learning fundamentals such as neural network architectures, sequence modeling, training dynamics, or optimization Proficiency in Python and modern machine learning frameworks such as PyTorch, Tensorflow, and/or JAX Demonstrated research excellence through publications, preprints, research internships, or significant research projects; publications at venues such as NeurIPS, ICML, ICLR, or equivalent conferences are highly preferred You may submit one application per role each year. We strongly encourage you to focus on applying to a single role that best matches your skills and interests. Though you may apply to multiple roles, please note that each application will be evaluated based on the specific criteria established for that particular role. If you have already applied for this position during the current recruitment season and were not selected, you may reapply when the next recruitment season begins in 2027. 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.