Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Build and optimise deep learning models for cutting-edge medical devices.
- Company: Exciting startup focused on innovative health monitoring technology.
- Benefits: Competitive salary, flexible work environment, and opportunities for growth.
- Why this job: Make a real impact in healthcare with state-of-the-art technology.
- Qualifications: MSc or PhD in ML or Biomedical Engineering; experience with PyTorch/TensorFlow.
- Other info: Join a dynamic team and help shape the future of health tech.
The predicted salary is between 36000 - 60000 £ per year.
Machine Learning Engineer
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 employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving PyTorch, TensorFlow, or TinyML. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and understanding model optimisation techniques. Practice common ML problems and be ready to discuss your past experiences in detail.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with PyTorch, TensorFlow, and any TinyML frameworks you've worked with. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're excited about working in a startup environment and how your background in ML or Biomedical Engineering makes you a perfect fit for our team.
Showcase Your Projects: If you've got hands-on experience with model optimization or edge deployment, make sure to include specific examples in your application. We love seeing real-world applications of your skills, so don’t hold back!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen on joining our team!
How to prepare for a job interview at Harnham
✨Know Your Tech Inside Out
Make sure you brush up on your knowledge of PyTorch, TensorFlow, and Python. Be ready to discuss your hands-on experience with TinyML or edge ML frameworks like TFLite and TVM. They’ll likely want to hear about specific projects where you’ve optimised models for constrained devices.
✨Show Your Startup Spirit
Since this is a startup environment, it’s crucial to demonstrate your proactive and adaptable nature. Share examples of how you've thrived in fast-paced settings before, and be prepared to discuss how you can contribute to shaping the direction of the company.
✨Collaborate Like a Pro
Collaboration is key, especially when working closely with the CTO and technical team. Think of instances where you’ve successfully worked in a team to deploy models in production. Highlight your communication skills and how you can bridge the gap between different areas of expertise.
✨Prepare for Technical Questions
Expect some deep-dive technical questions related to model compression, quantization, and edge deployment techniques. Practise explaining these concepts clearly and concisely, as well as any challenges you faced and how you overcame them in past projects.
