Machine Learning Engineer in London

Machine Learning Engineer in London

London Full-Time 59400 - 72600 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Build and integrate ML models for real-time interactive gaming experiences.
  • Company: Join Iconic Interactive, an innovative AI-native game development studio.
  • Benefits: Competitive salary, equity, 25 days leave, private healthcare, and hybrid working.
  • Other info: Be part of a friendly culture with game breaks and exciting team socials.
  • Why this job: Shape the future of gaming with cutting-edge AI technology and creative collaboration.
  • Qualifications: Strong Python skills and experience with ML models in PyTorch or JAX.

The predicted salary is between 59400 - 72600 £ per year.

This is a hybrid role (3 days per week) based out of London.

Iconic Interactive is an AI-native game development and research studio exploring the future of interactive entertainment, digital actors, and intelligent worlds.

We’re looking for an experienced Machine Learning engineer to join our team, focused on building custom, efficient models and integrations to power real-time interaction for the next generation of games and interactive experiences.

As part of a small, focused team, you'll have significant autonomy and end-to-end ownership over design and implementation.

You’ll work closely with artists, writers and designers as well as the rest of the engineering team to build systems that actually translate into creative & fun games.

What You’ll Do

  • Build, train and integrate ML models for real-time interactive experiences
  • Own projects across the ML pipeline, from experimentation through to production
  • Optimise models for performance, latency and efficiency
  • Work with engineering and creative teams to turn ML capabilities into compelling experiences

What We’re Looking For

  • Strong knowledge of Python
  • Experience writing models in Py Torch or JAX
  • A good understanding of how large language models work
  • Comfortable working along the whole ML pipeline: from data preparation to model design, training and evaluation, and shipping in products
  • Degree in Computer Science or a related field, or equivalent industry or personal experience (show us your personal projects!)

Nice to Have

  • Experience building agent harnesses or user-facing systems based on LLMs
  • Experience shipping machine learning models on consumer devices or edge compute
  • Experience optimising, quantising or writing kernels for LLMs
  • Knowledge of C/C++, or experience with Unreal Engine, Unity or similar game engines
  • Experience with managing ML environments and hardware
  • Experience working with audio models or other multi-modal models.
  • An appreciation for game design and development principles

The ideal candidate is unlikely to have all the above, so if you have any, we would love to hear from you.

Why Join Us

Be a foundational member of a team innovating at the intersection of AI, games, art and storytelling.

You’ll help shape the technical foundations of a company building toward something genuinely new.

What We Offer

  • Competitive salary and equity compensation
  • 25 days annual leave + bank holidays
  • Private healthcare
  • London-based hybrid working
  • Inclusive & friendly company culture with socials and game breaks

Machine Learning Engineer in London employer: Iconic

At Iconic Interactive, we pride ourselves on being an exceptional employer, offering a unique opportunity to work at the forefront of AI-driven game development in the vibrant city of London. Our inclusive and friendly culture fosters collaboration and creativity, while our commitment to employee growth is reflected in our competitive salary, equity compensation, and generous leave policies. Join us to be part of a small, focused team where your contributions will directly shape the future of interactive entertainment.

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Contact Details:

Iconic Recruitment Team

StudySmarter Expert Advice🤫

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

Join Local Tech Meetups

Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Iconic or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!

Contribute to Open Source Projects

Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Iconic.

Tap into Online Developer Communities

Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Iconic.

Explore Job Boards Specifically for Tech Roles

Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Iconic that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!

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

Python
PyTorch
JAX
Machine Learning Pipeline
Model Design
Model Training
Model Evaluation

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Iconic.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Iconic and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at Iconic

Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Iconic uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.