Principal ML Engineer in London

Principal ML Engineer in London

London Full-Time 80000 - 180000 £ / year (est.) Working from home possible
McGregor Boyall

At a Glance

  • Tasks: Design and deploy cutting-edge machine learning systems for a revolutionary AI assistant.
  • Company: Exciting stealth AI startup with a focus on innovation and collaboration.
  • Benefits: Competitive salary, equity options, and fully remote work across Europe.
  • Other info: Opportunity for mentorship and leadership in a fast-paced, dynamic environment.
  • Why this job: Join a high-calibre team and shape the future of AI technology from day one.
  • Qualifications: Experience in building production ML systems and strong Python skills required.

The predicted salary is between 80000 - 180000 £ per year.

Senior Machine Learning Engineer

Location: Fully Remote (Europe)

Salary: £80,000 - £180,000 + Equity

The Role

I'm working with a well‑funded, stealth AI company building a next‑generation AI assistant designed to help people manage everyday tasks, conversations and workflows. The product is still pre‑launch, making this a genuine 0–1 opportunity to join a small, high‑calibre engineering team and build the machine learning systems that will power the product from day one. They're hiring across multiple levels, from Senior through to Staff Machine Learning Engineers.

Key Responsibilities

  • Design, build and deploy production machine learning systems
  • Own the full ML lifecycle, from data preparation through to training, evaluation and inference
  • Turn research into reliable, production-ready ML solutions
  • Optimise models for performance, latency, scalability and cost
  • Build robust training and inference pipelines
  • Debug complex production issues using real‑world data and signals
  • Mentor engineers and help drive engineering standards across the ML function

Key Requirements

  • Commercial experience building and deploying production ML systems
  • Strong Python software engineering skills
  • Experience training, fine‑tuning or deploying modern machine learning models
  • Strong experience with PyTorch and/or JAX
  • Experience building scalable ML infrastructure and inference pipelines
  • Comfortable owning projects end-to-end in fast-moving environments
  • Previous mentoring or technical leadership experience would be advantageous

Tech Stack

Python, PyTorch, JAX, GPU Training, LLMs, Modern ML Infrastructure

Get in touch for more details.

Principal ML Engineer in London employer: McGregor Boyall

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McGregor Boyall

Contact Details:

McGregor Boyall Recruitment Team

StudySmarter Expert Advice🤫

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

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Apply Directly through Our Website

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

Machine Learning Systems Design
Production ML Deployment
Data Preparation
Model Training and Evaluation
Performance Optimisation
Scalability and Cost Management
Robust Pipeline Development

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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Craft a Tailored Cover Letter:For a full-time role at McGregor Boyall, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at McGregor Boyall. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at McGregor Boyall

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

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Get Comfortable with Python and R

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Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.