Machine Learning Engineer
AI in this role
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.
How we rate this
Machine Learning Engineer at IMC rates 100 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- What's a project where you used PyTorch hands-on?
- Walk me through how you've used TensorFlow in your day-to-day work.
- What are the limits of Jax that you've run into, and how did you work around them?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: PyTorch, TensorFlow, and Jax. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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