Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Build and deploy cutting-edge ML solutions for real customer processes.
- Company: Venture-backed AI company focused on innovative customer solutions.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Join a dynamic team and make a real impact with AI technology.
- Qualifications: Strong ML and software engineering skills, proficient in Python.
- Other info: Exciting projects with potential for career advancement in a fast-paced environment.
The predicted salary is between 48000 - 72000 £ per year.
We’re representing a venture-backed AI company hiring a Senior Machine Learning Engineer to deliver production ML solutions for enterprise customers. This role focuses on building and deploying end-to-end ML workflows that automate real customer processes.
Key Responsibilities
- Build and deploy ML solutions into production
- Translate customer requirements into deliverable technical work
- Improve tooling to scale repeatable customer delivery
- Partner with engineering/product teams to ship AI capabilities
Requirements
- Strong production ML + software engineering experience
- Proficient in Python
- Comfortable owning projects end-to-end
- Strong communication and stakeholder management skills
Nice to Have
- Computer vision / image-video ML experience
- Enterprise deployments and MLOps exposure
Machine Learning Engineer (Customers) employer: Understanding Recruitment
Contact Detail:
Understanding Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer (Customers)
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow Machine Learning enthusiasts. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Showcase your skills! Create a portfolio of your projects, especially those involving production ML solutions. This will not only demonstrate your expertise but also give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python skills and understanding end-to-end ML workflows. Practice coding challenges and be ready to discuss your past projects in detail—this is where we can really shine!
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Keep an eye on our job listings and make sure your application stands out by tailoring it to the specific role.
We think you need these skills to ace Machine Learning Engineer (Customers)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your production ML and software engineering experience. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects you've worked on!
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 you can contribute to our team. Remember, we love seeing your personality come through!
Showcase Your Projects: If you’ve built or deployed any ML solutions, make sure to mention them! We’re keen on seeing your end-to-end project ownership, so include links or descriptions of your work that demonstrate your capabilities.
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’s super easy!
How to prepare for a job interview at Understanding Recruitment
✨Know Your ML Stuff
Make sure you brush up on your machine learning concepts and production experience. Be ready to discuss specific projects you've worked on, especially those that involved end-to-end workflows. This will show that you can translate customer requirements into practical solutions.
✨Show Off Your Python Skills
Since proficiency in Python is a must-have, be prepared to demonstrate your coding skills. You might be asked to solve a problem on the spot or discuss your approach to building ML solutions. Practising common algorithms and libraries can give you an edge.
✨Communicate Like a Pro
Strong communication is key, especially when it comes to stakeholder management. Practice explaining complex technical concepts in simple terms. This will help you connect with non-technical team members and show that you can effectively partner with engineering and product teams.
✨Get Familiar with MLOps
If you have any experience with MLOps or enterprise deployments, make sure to highlight it. Even if it's just a nice-to-have, showing that you understand the deployment process and tooling can set you apart from other candidates. Do some research on current best practices to discuss during the interview.
