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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 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.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.