Principal Machine Learning Engineer in London
Principal Machine Learning Engineer

Principal Machine Learning Engineer in London

London Full-Time 160000 - 200000 £ / year (est.) Home office (partial)
IMC Trading

At a Glance

  • Tasks: Design and build cutting-edge ML infrastructure for trading systems.
  • Company: IMC, a global trading firm with a collaborative culture.
  • Benefits: Competitive salary, bonuses, paid leave, and comprehensive insurance.
  • Other info: Work globally with diverse teams and enjoy excellent career growth opportunities.
  • Why this job: Shape the future of trading with innovative ML solutions and direct impact.
  • Qualifications: 8+ years in ML platforms, strong Python skills, and deep learning expertise.

The predicted salary is between 160000 - 200000 £ per year.

At IMC, we believe technology is the foundation of our competitive edge — and machine learning is increasingly central to how we trade. Over the past few years, we've been steadily building our machine learning capabilities: developing infrastructure, growing our in-house GPU cluster, deploying models into production, and partnering closely with quant researchers and traders to generate real impact. We’re expanding the team, scaling our systems, and accelerating the application of deep learning in our research and execution workflows. We’re looking for a Principal Machine Learning Engineer to help shape the next phase of our platform — influencing architecture, driving best practices, and solving high-leverage problems.

Your Core Responsibilities:

  • Design and build end-to-end infrastructure for training, evaluation, and productionization of ML models, working closely with our HPC engineers who manage our on-prem compute cluster.
  • Influence foundational choices around data access, compute orchestration, experiment tracking, model versioning, and deployment pipelines.
  • Partner with quant researchers to accelerate iteration cycles, tighten feedback loops, and bring models from prototype to live trading.
  • Work with researchers to adapt and deploy modern architectures — transformers, state-space models, temporal convolutions, graph neural networks — to noisy, high-frequency financial data.
  • Explore techniques like self-supervised pretraining, representation learning, and cross-sectional modelling where they offer genuine edge.
  • Shape our approach to reproducibility, continual learning, and production monitoring across a petabyte-scale data environment.
  • Define standards that create consistency across teams and geographies; mentor engineers and influence technical culture beyond your immediate work.
  • Keep pace with developments in deep learning research and ML infrastructure; bring ideas from academia and industry into how we work — whether that’s new architectures, training techniques, or tooling.

Your Skills And Experience:

  • 8+ years of experience building ML platforms or infrastructure at a leading tech company, research lab, or quantitative firm.
  • A track record of designing and owning large-scale training and inference systems — not just contributing, but architecting.
  • Deep proficiency in Python, with strong experience in either CUDA or C++.
  • Hands-on expertise with modern deep learning frameworks (PyTorch, TensorFlow, or JAX) and practical experience implementing architectures like transformers, attention mechanisms, or sequence models.
  • Strong foundation in deep learning fundamentals: optimization, regularization, loss design, and the trade-offs that matter when training at scale.
  • Experience with distributed training at scale (Horovod, NCCL) and GPU optimization (cuDNN, TensorRT).
  • History of deploying models to production with strong observability, reproducibility, and monitoring practices.
  • Comfort working across the ML stack from data pipelines to training infrastructure to serving systems.

Why This Role:

  • Build, don’t inherit — You’ll make foundational technology choices in a platform that’s still being defined, not maintain someone else’s legacy.
  • Real investment, real backing — This is a strategic priority with resources behind it, not a side experiment.
  • Direct impact on trading — Your infrastructure will power models that make real trading decisions in competitive global markets.
  • Global scope — Work with teams across New York, Chicago, Amsterdam, London, Sydney, Hong Kong and beyond; define practices that can scale worldwide.
  • Ideas over titles — IMC’s culture values clarity, rigor, and collaboration. The best ideas win, regardless of where they come from.
  • Tight coupling with research — You won’t be building in isolation. Researchers and engineers work side-by-side, iterating together.

The Base Salary range for the role is included below. Base salary is only one component of total compensation; all full-time, permanent positions are eligible for a discretionary bonus and benefits, including paid leave and insurance.

Salary Range: $200,000 - $250,000 USD

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.

Principal Machine Learning Engineer in London employer: IMC Trading

At IMC, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters collaboration and innovation. As a Principal Machine Learning Engineer, you'll have the opportunity to shape cutting-edge technology in a global trading firm, with access to extensive resources and a commitment to employee growth through mentorship and cross-team collaboration. Our supportive environment encourages you to bring your ideas to the forefront, making a tangible impact on our trading strategies while enjoying competitive compensation and comprehensive benefits.
IMC Trading

Contact Detail:

IMC Trading Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Principal Machine Learning Engineer in London

✨Tip Number 1

Network like a pro! Reach out to folks in the industry, especially those at IMC or similar firms. A friendly chat can open doors and give you insights that might just land you an interview.

✨Tip Number 2

Show off your skills! Create a portfolio showcasing your ML projects, especially those involving large-scale systems. This is your chance to demonstrate your expertise and creativity in action.

✨Tip Number 3

Prepare for technical interviews by brushing up on your deep learning fundamentals and coding skills. Practice solving problems on platforms like LeetCode or HackerRank to get into the right mindset.

✨Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team.

We think you need these skills to ace Principal Machine Learning Engineer in London

Machine Learning Infrastructure
Deep Learning Frameworks (PyTorch, TensorFlow, JAX)
Python
CUDA or C++
Transformers
Attention Mechanisms
Sequence Models
Distributed Training (Horovod, NCCL)
GPU Optimisation (cuDNN, TensorRT)
Model Deployment
Experiment Tracking
Data Pipelines
Reproducibility
Monitoring Practices
Collaboration with Researchers

Some tips for your application 🫡

Tailor Your Application: Make sure to customise your CV and cover letter for the Principal Machine Learning Engineer role. Highlight your experience with ML infrastructure and any relevant projects that showcase your skills in Python, CUDA, or C++. We want to see how your background aligns with our needs!

Showcase Your Impact: When detailing your past experiences, focus on the impact you've made. Did you design a system that improved efficiency? Or perhaps you led a project that significantly reduced model training time? We love to see quantifiable results that demonstrate your contributions.

Be Clear and Concise: Keep your application clear and to the point. Use straightforward language and avoid jargon unless it's necessary. We appreciate a well-structured application that makes it easy for us to see your qualifications and enthusiasm for the role.

Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it gives you a chance to explore more about IMC and what we stand for.

How to prepare for a job interview at IMC Trading

✨Know Your ML Infrastructure Inside Out

Make sure you can discuss your experience with building and scaling ML platforms. Be ready to share specific examples of how you've designed end-to-end systems for training and deploying models, especially in high-frequency environments.

✨Brush Up on Modern Architectures

Familiarise yourself with the latest deep learning architectures like transformers and graph neural networks. Be prepared to explain how you've implemented these in past projects and how they can be applied to financial data.

✨Showcase Your Collaboration Skills

Since this role involves working closely with quant researchers, highlight your experience in cross-functional teams. Share examples of how you've partnered with others to accelerate iteration cycles and improve model performance.

✨Stay Current with Industry Trends

Keep up with the latest developments in deep learning and ML infrastructure. Be ready to discuss recent research or tools that could benefit IMC's approach, showing that you're not just knowledgeable but also passionate about the field.

Principal Machine Learning Engineer in London
IMC Trading
Location: London

Land your dream job quicker with Premium

You’re marked as a top applicant with our partner companies
Individual CV and cover letter feedback including tailoring to specific job roles
Be among the first applications for new jobs with our AI application
1:1 support and career advice from our career coaches
Go Premium

Money-back if you don't land a job in 6-months

>