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- Tasks: Deploy and optimise machine-learning models in a dynamic gaming environment.
- Company: Fully remote gaming and entertainment business with a data-driven culture.
- Benefits: Up to £90,000 salary, flexible remote work, and great benefits.
- Why this job: Join a cutting-edge team and make an impact in the gaming industry.
- Qualifications: Experience with ML systems and strong coding skills are essential.
- Other info: No strict experience requirements; perfect for problem solvers.
The predicted salary is between 54000 - 126000 £ per year.
Fully Remote - UK based
Up to £90,000 + Benefits
About the Role
We are working with a fully remote gaming and entertainment business that is scaling its data and machine-learning capabilities. With strong backing for data-driven decision-making, they are now looking for a Machine Learning Engineer to help operationalise, maintain, and optimise their ML systems across the organisation. This position is ideal for someone who is strong technically, resilient, enjoys problem-solving in ambiguous environments, and wants to work closely with both Data Scientists and Engineers.
Key Responsibilities
- Deploy, productionise, and monitor machine-learning models across the business.
- Maintain and improve ML infrastructure to ensure high reliability, scalability, and runtime performance.
- Collaborate with data scientists to ensure smooth model handover from prototype to production.
- Work alongside data engineers, supporting but not owning data-engineering pipelines.
- Build tooling, automation, and monitoring systems to support long-term ML lifecycle management.
- Ensuring live models perform consistently in a high-volume environment.
- Streamlining the deployment process and improving ML observability.
- Supporting automated decision systems across game-economy and player-behaviour use cases.
What We’re Looking For
- Experience deploying, monitoring, and maintaining ML systems in production environments.
- Strong understanding of cloud platforms (GCP preferred) and containerisation/orchestration tools.
- Solid coding ability, with experience building reliable and scalable infrastructure.
- Excellent problem-solving skills and comfort operating within a fast-moving environment.
- No strict requirements on years of experience or academic background.
If this looks of interest, please apply below.
Machine Learning Engineer in Edinburgh employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer in Edinburgh
✨Tip Number 1
Network like a pro! Reach out to folks in the gaming and machine learning space on LinkedIn or at industry events. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects. Whether it's a GitHub repo or a personal website, let your work speak for itself.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss how you've tackled real-world problems. Practice makes perfect, so do mock interviews with friends.
✨Tip Number 4
Don't forget to apply through our website! We love seeing applications directly from candidates who are excited about joining us. It shows initiative and enthusiasm!
We think you need these skills to ace Machine Learning Engineer in Edinburgh
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your experience with deploying and maintaining ML systems, and don’t forget to mention any cloud platforms you’ve worked with, especially GCP!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about machine learning and how your skills align with our needs. Be sure to mention your problem-solving abilities and your experience in fast-paced environments.
Showcase Your Projects: If you’ve worked on any relevant projects, make sure to include them! Whether it’s a personal project or something from a previous job, showcasing your hands-on experience with ML models can really set you apart.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and we love seeing applications come directly from interested candidates like you!
How to prepare for a job interview at Harnham
✨Know Your ML Stuff
Make sure you brush up on your machine learning concepts and frameworks. Be ready to discuss your experience with deploying and maintaining ML systems, especially in production environments. Familiarity with cloud platforms like GCP and containerisation tools will definitely give you an edge.
✨Showcase Problem-Solving Skills
Prepare to share specific examples of how you've tackled complex problems in ambiguous situations. Think about times when you had to optimise ML models or improve infrastructure reliability. This will demonstrate your resilience and ability to thrive in a fast-paced environment.
✨Collaboration is Key
Since the role involves working closely with data scientists and engineers, be ready to discuss your collaborative experiences. Highlight any projects where you successfully handed over models from prototype to production, and how you supported data engineers without owning the pipelines.
✨Ask Insightful Questions
Prepare some thoughtful questions about the company's ML systems and their approach to data-driven decision-making. This shows your genuine interest in the role and helps you understand how you can contribute to their goals, especially in streamlining deployment processes and improving observability.
