Graduate Machine Learning Researcher - London

IMC; Greater London; On-site; GBP 42,000 - 60,000; Full time

Job summary

IMC is seeking a Graduate Machine Learning Researcher in London to design and deploy ML models for trading across global equities, futures, and options. You will work with traders, researchers, and engineers to translate research into production systems, using PyTorch and Python with a strong statistical foundation.

The role targets final-year students graduating in 2027, with MSc or PhD in quantitative fields. No finance experience required, and the start window includes February or August 2027.

Qualifications

• Final year student graduating in 2027 with an MSc or PhD in a quantitative field.
• Strong foundations in statistics and machine learning with a research track record.
• Proficiency in PyTorch and Python.
• Publications in respected journals covering deep learning or time-series modeling valued.
• No prior finance knowledge required.

Responsibilities

• Design, implement, and evaluate ML models for trading applications with production deployment.
• Apply rigorous statistical techniques to measure performance and control overfitting.
• Investigate novel ML approaches through rigorous experimentation in real trading environments.
• Communicate research progress and outcomes across the team and departments.
• Collaborate with traders, researchers, and engineers to translate research into production trading systems.

Skills

Final year student

MSc/PhD in ML

PyTorch

Python

Statistics

Time-series modeling

Publications in journals

Education

MSc in ML or related

PhD preferred

Tools

PyTorch

Python

Job description

As a Graduate Machine Learning Researcher at IMC, your work will directly impact our global trading strategies. You will apply advanced machine learning, statistical, and computational techniques to solve complex, real-world trading problems, contributing to trading strategies across global equities, futures, and options markets. Machine Learning Researchers work closely with Traders and Developers in an environment where problem solving, innovation and teamwork are recognized and rewarded.

Your Core Responsibilities:

• Design, implement, and evaluate machine learning models for trading applications, with successful research deployed into production

• Apply rigorous statistical techniques to measure performance, control overfitting, and understand model risk and interpretability

• Investigate novel machine learning approaches through rigorous experimentation and analysis in real trading environments

• Communicate research progress and outcomes effectively, ensuring knowledge transfer within the team and across departments

• Collaborate closely with traders, researchers, and engineers to translate research into production trading systems

Your Skills and Experience:

• Currently in your final year of study, graduating in 2027

• A minimum of an MSc (PhD preferred) in Machine Learning, Statistics, Deep Learning, Probabilistic Programming, or a related quantitative field

• Strong foundations in statistics and machine learning, with a demonstrated research track record in ML, deep learning, or another quantitative field

• Proficiency in fundamental ML frameworks like Pytorch and experience in Python

• Solid understanding of statistics

• Desirable: publications in respected journals covering deep learning or time-series modeling

• No prior finance knowledge or experience required

• Ability to commence full-time employment in February or August 2027

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.