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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 comprehensive benefits.
- Why this job: Join a cutting-edge team and make an impact in the gaming industry.
- Qualifications: Experience with ML systems and cloud platforms; strong coding and problem-solving skills.
- Other info: No strict experience requirements; perfect for tech-savvy 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 Glasgow employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer in Glasgow
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for those interviews! Brush up on common ML concepts and be ready to discuss your past experiences. Practising with friends or using mock interview platforms can really help.
✨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, we love hearing from passionate candidates like you!
We think you need these skills to ace Machine Learning Engineer in Glasgow
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. They’ll want to know how you’ve tackled challenges in the past, so have some examples up your sleeve!
✨Cloud and Container Knowledge
Since they prefer GCP and containerisation tools, it’s a good idea to familiarise yourself with these platforms. Be prepared to talk about how you've used cloud services in your previous roles and any specific projects where you’ve implemented container orchestration.
✨Collaboration is Key
This role involves working closely with data scientists and engineers, so highlight your teamwork skills. Think of examples where you’ve successfully collaborated on projects, particularly around model handovers or improving ML infrastructure.
✨Problem-Solving Mindset
They’re looking for someone who thrives in ambiguous situations. Prepare to discuss how you approach problem-solving, especially in fast-paced environments. Share stories that showcase your resilience and ability to adapt when things don’t go as planned.
