Machine Learning Engineer

Job Title: Machine Learning Engineer Company: IMC Trading Job Category: Machine Learning Roles & Responsibilities: Machine Learning Engineers at IMC play a pivotal role in building the systems that drive training and deployment of large\-scale ML models across IMC's global operations. They collaborate with quantitative researchers, hardware specialists and software engineers to build robust systems that get the most out of GPU acceleration, distributed computing and the broader open\-source ML ecosystem. ML Engineers' work directly shapes how fast we can experiment, iterate and deploy, accelerating the cycle that turns a research idea into a live trading strategy. Your Core Responsibilities ML Research Engineering: * Develop large\-scale distributed training pipelines that manage complex datasets and models. * Partner with quantitative researchers to automate ML experiments, hyperparameter tuning and model retraining. * Work with HPC specialists to optimise workflows, improve training speed and reduce compute cost. Across Both Areas * Extend and improve the internals of machine learning frameworks and open\-source tools to raise their performance for our workloads. * Design scalable model infrastructure capable of handling high\-volume trading data and delivering real\-time, high\-accuracy predictions. * Evaluate and roll out third\-party tools that enhance model development, training and inference capabilities. 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. Work Location: Sydney, New South Wales, Australia Availability: Full time

Your Skills And Experience Core, regardless of focus area: Depth In One Or More Of The Following * Distributed training and large\-scale systems: parallelism strategy, data pipelines and checkpointing; frameworks such as PyTorch, TensorFlow or JAX. * GPU performance and low\-level optimisation: reasoning about memory, compute and latency at the device level, and optimising performance across kernels, compilers and hardware (e.g. CUDA, Triton or equivalent). * Production inference systems: hands\-on experience building and hardening real\-time, low\-latency prediction pipelines in high\-performance environments. * Numerics and correctness at scale: low\-precision effects, KV caching, batching, and knowing which optimisations stay bit\-exact. Key Skills: Machine Learning, Python, TensorFlow, PyTorch Salary: Not disclosed