At a Glance
- Tasks: Build and deploy large-scale ML models that drive innovation in trading.
- Company: IMC, a global trading firm with a cutting-edge tech environment.
- Benefits: Competitive salary, collaborative culture, and opportunities for professional growth.
- Other info: Join a dynamic team committed to continuous innovation and collaboration.
- Why this job: Shape the future of trading technology while working with top experts in the field.
- Qualifications: 5+ years in machine learning, strong Python/CUDA skills, and experience with real-time ML pipelines.
The predicted salary is between 70000 - 90000 £ per year.
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.
Machine Learning Engineer in London employer: IMC
IMC is an excellent employer for Locum Echocardiographers, offering a supportive work culture that values collaboration and professional growth. Located in Worthing, you will enjoy competitive hourly rates and the flexibility of locum work, allowing you to balance your career with personal commitments while making a meaningful impact in cardiology services.
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We think you need these skills to ace Machine Learning Engineer in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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