At IMC, technology is not a department it’s at the heart of everything we do. Our in-house built systems make millions of trading decisions every day, and our edge comes from making better, faster decisions than the competition.

Our engineers build software that sits directly in the latency-critical path of our trading systems. From exchange connectivity and market data handling to pricing, risk management, and order execution, our technology underpins every part of the trading lifecycle. In Hong Kong, you’ll work closely with Traders and Quant Researchers to develop high-performance systems that operate at scale in highly competitive global markets.

Your Core Responsibilities: 

As a C++ Engineer, you will design and build performance-critical components that power our trading systems, working in close partnership with Traders, Researchers, and other engineers.

• Design, build and optimise high-performance C++ trading systems that power pricing, risk management and order strategy across equities markets, ensuring robust and scalable performance in live trading environments.
• Work closely with Traders and Quant Researchers to translate trading ideas into efficient, production-ready systems
• Continuously improve system performance through profiling, optimisation, and thoughtful systems design
• Own the full development lifecycle, from design and implementation through to deployment and monitoring
• Navigate complex trade-offs between latency, throughput, scalability, and maintainability in a real-time environment

Your Skills and Experience: 

• Strong programming skills in C++. Experience in latest versions of C++ highly desirable
• Solid understanding of systems programming concepts, including concurrency, memory management, and performance optimisation
• Experience working in Linux environments
• Proven ability to build and optimise high-performance systems
• A high degree of flexibility and adaptability: willing and able to deal with uncertainty and ambiguity in a rapidly evolving environment
• Comfortable working closely with stakeholders to deliver impactful solutions

#LI-DNI

IMC is hiring a Quantitative Trader to focus on monetization research and back testing for high- to mid-frequency delta-one equity strategies. This role emphasizes research depth, systematic evaluation, and capital efficiency, partnering closely with quant researchers and engineers to turn signals into scalable, profitable trading strategies.

Based in Sydney, this role is ideal for candidates who excel at research-driven trading problems, large-scale data analysis, and rigorous performance validation. For exceptional candidates from top global trading firms, Hong Kong location may be considered.

Core Responsibilities

• Research and evaluate new trading signals and strategy ideas with a focus on monetization potential
• Design and run large-scale back tests to assess PnL, risk, capacity, and robustness
• Analyse transaction costs, market impact, and execution assumptions within back testing frameworks
• Optimize portfolio construction, capital allocation, and risk controls across strategies
• Work with engineers to improve back testing infrastructure, data quality, and research tooling
• Partner with live traders to ensure research assumptions align with real-world execution behaviour
• Drive strategies from research validation through production readiness

Skills & Experience

• Degree in a quantitative field (Mathematics, Physics, Computer Science, Engineering, Economics, or similar)
• 3+ years of experience in quantitative trading or monetization research, preferably in equities
• Strong experience with back testing frameworks, large datasets, and systematic performance evaluation
• Deep understanding of market microstructure, transaction costs, and scalability constraints
• Strong programming skills (Python/C++ strongly preferred); ability to write clean, research-grade code
• Rigorous, detail-oriented mindset with strong statistical intuition
• Experience at leading systematic or proprietary trading firms is a strong plus

IMC is seeking an experienced Quantitative Trader to focus on live trading operations and performance analysis for high to mid-frequency, delta-one equity strategies in APAC markets. Based in Hong Kong, this role sits close to production trading and is responsible for maximizing PnL through real-time monitoring, execution optimization, and rapid feedback loops between trading, research, and engineering.

This is a hands-on trading role with strong ownership of day-to-day strategy behaviour in live markets, requiring sound judgment under pressure and deep understanding of market microstructure.

Core Responsibilities

• Operate and oversee live high- to mid-frequency equity trading strategies across APAC markets
• Monitor intraday performance, risk, and execution quality; identify and act on anomalies in real time
• Analyse fills, slippage, adverse selection, and market impact to continuously improve execution outcomes
• Work closely with quant researchers to translate research ideas into robust, production-ready trading behaviour
• Partner with engineers to diagnose production issues, improve system stability, and enhance trading infrastructure
• Contribute to post-trade analysis, performance attribution, and feedback into strategy iteration
• Ensure strategies operate within defined risk limits and respond appropriately to changing market conditions

Skills & Experience

• Degree in a quantitative field (Mathematics, Physics, Computer Science, Engineering, Economics, or similar)
• 3+ years of experience in systematic equity trading, with direct exposure to live trading environments
• Strong understanding of market microstructure, order books, and execution dynamics in APAC markets
• Proven experience analysing execution quality, market impact, and intraday performance drivers
• Strong programming and data analysis skills (Python/C++ strongly preferred)
• Ability to make sound decisions under pressure and manage multiple live priorities simultaneously
• Excellent communication skills and a collaborative, team-oriented mindset

IMC is looking for experienced quant researchers to develop high 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 behavior. 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: 

• Combine creativity and experience to rapidly generate high quality, testable ideas
• Use a rigorous and structured process to ensure your results are reliable and well tested
• Refine and leverage a strong grasp of market dynamics and microstructure, to create powerful features
• Have a solid understanding of statistics, a variety of machine learning approaches, and the risks of overfitting

Your Skills and Experience: 

• 3+ years experience as a Quantitative Researcher or Trader, with specific experience in high frequency Equities or Futures, and a proven track record
• Graduate & Postgraduate study from a top university, majoring in machine learning, statistics, or STEM subjects
• Strong programming skills in at least one language (python preferred)
• Significant practical experience with at least one mainstream ML approach

About Us

IMC is a global trading firm powered by a cutting-edge research environment and a world-class technology backbone. Since 1989, we’ve been a stabilizing force in financial markets, providing essential liquidity upon which market participants depend. Across our offices in the US, Europe, Asia Pacific, and India, our talented quant researchers, engineers, traders, and business operations professionals are united by our uniquely collaborative, high-performance culture, and our commitment to giving back. From entering dynamic new markets to embracing disruptive technologies, and from developing an innovative research environment to diversifying our trading strategies, we dare to continuously innovate and collaborate to succeed.

At IMC, we believe technology is the foundation of our competitive edge — and machine learning is increasingly central to how we trade. Over the past few years, we've been steadily building our machine learning capabilities: developing infrastructure, growing our in-house GPU cluster, deploying models into production, and partnering closely with quant researchers and traders to generate real impact. Now we’re expanding the team, scaling our systems, and accelerating the application of deep learning in our research and execution workflows.  We're looking for a Principal Machine Learning Engineer to help shape the next phase of our platform — influencing architecture, driving best practices, and solving high-leverage problems. You’ll work alongside researchers and technologists to design the systems that power experimentation, training, and deployment of ML models — and help set the direction for how machine learning is done at IMC as we scale. If you’ve built ML infrastructure at scale elsewhere and are looking for a role where your ideas will genuinely help shape our firm’s future — we’d love to hear from you.

Your Core Responsibilities: 

• Design and build end-to-end infrastructure for training, evaluation, and productionization of ML models, working closely with our HPC engineers who manage our on-prem compute cluster
• Influence foundational choices around data access, compute orchestration, experiment tracking, model versioning, and deployment pipelines
• Partner with quant researchers to accelerate iteration cycles, tighten feedback loops, and bring models from prototype to live trading
• Work with researchers to adapt and deploy modern architectures — transformers, state-space models, temporal convolutions, graph neural networks — to noisy, high-frequency financial data. Explore techniques like self-supervised pretraining, representation learning, and cross-sectional modelling where they offer genuine edge
• Shape our approach to reproducibility, continual learning, and production monitoring across a petabyte-scale data environment
• Define standards that create consistency across teams and geographies; mentor engineers and influence technical culture beyond your immediate work
• Keep pace with developments in deep learning research and ML infrastructure; bring ideas from academia and industry into how we work — whether that's new architectures, training techniques, or tooling

Your Skills and Experience: 

• 8+ years of experience building ML platforms or infrastructure at a leading tech company, research lab, or quantitative firm
• A track record of designing and owning large-scale training and inference systems — not just contributing, but architecting
• Deep proficiency in Python, with strong experience in either CUDA or C++
• Hands-on expertise with modern deep learning frameworks (PyTorch, TensorFlow, or JAX) and practical experience implementing architectures like transformers, attention mechanisms, or sequence models
• Strong foundation in deep learning fundamentals: optimization, regularization, loss design, and the trade-offs that matter when training at scale
• Experience with distributed training at scale (Horovod, NCCL) and GPU optimization (cuDNN, TensorRT)
• History of deploying models to production with strong observability, reproducibility, and monitoring practices
• Comfort working across the ML stack from data pipelines to training infrastructure to serving systems

Why This Role: 

• Build, don't inherit — You'll make foundational technology choices in a platform that's still being defined, not maintain someone else's legacy.
• Real investment, real backing — This is a strategic priority with resources behind it, not a side experiment.
• Direct impact on trading — Your infrastructure will power models that make real trading decisions in competitive global markets.
• Global scope — Work with teams across New York, Chicago, Amsterdam, London, Sydney, Hong Kong and beyond; define practices that can scale worldwide.
• Ideas over titles — IMC's culture values clarity, rigor, and collaboration. The best ideas win, regardless of where they come from.
• Tight coupling with research — You won't be building in isolation. Researchers and engineers work side-by-side, iterating together.

#LI-DNP

IMC is looking for experienced quant researchers to develop high frequency delta one trading strategies and predictive models for the China Commodity Futures & Options market. 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: 

• Combine creativity and experience to rapidly generate high quality, testable alpha signals
• Refine and leverage deep understanding of market microstructure and order book dynamics in China & global Commodity Futures, to create powerful features
• Apply statistical and machine learning techniques with strong discipline around robustness and overfitting
• Collaborate closely with trading and engineering teams to translate research into production strategies

Your Skills and Experience: 

• 3+ years of experience in high-frequency alpha research for China Commodity Futures, with strong track record
• Strong foundation in probability and statistics, and significant practical experience with at least one mainstream ML approach
• Experience working with large, high-frequency trading datasets
• Excellent programming skills in at least one language (Python preferred)
• Practical mindset with a focus on deployable, real-world edge

IMC is looking for experienced quant researchers to develop high 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: 

• Combine creativity and experience to rapidly generate high quality, testable alpha signals
• Refine and leverage deep understanding of market microstructure and order book dynamics, to create powerful features
• Apply statistical and machine learning techniques with strong discipline around robustness and overfitting
• Collaborate closely with trading and engineering teams to translate research into production strategies

Your Skills and Experience: 

• 3+ years of experience in high-frequency equities or futures alpha research, ideally with prior track record in at least one of the Asia markets
• Strong foundation in probability and statistics, and significant practical experience with at least one mainstream ML approach
• Experience working with large, high-frequency trading datasets
• Excellent programming skills in at least one language (Python preferred)
• Practical mindset with a focus on deployable, real-world edge

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

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: 

• 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

#LI-DNP