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- Tasks: Build and deploy cutting-edge ML solutions for customer-facing products.
- Company: Join a forward-thinking tech company with a focus on innovation.
- Benefits: Earn up to £70,000, enjoy 35 days holiday, and great perks.
- Why this job: Take ownership of exciting ML projects and make a real impact.
- Qualifications: Strong Python skills and hands-on AWS experience required.
- Other info: Flexible hybrid working and a budget for your learning and wellbeing.
The predicted salary is between 42000 - 84000 £ per year.
We’re hiring a Machine Learning Engineer to build and deploy production ML solutions embedded directly into customer-facing products. This is a hands‑on, end‑to‑end role with ownership from requirements through to live client delivery.
You’ll be asked to:
- Design, build, and deploy ML solutions from specification to production
- Implement ML features within live products used by clients
- Write high-quality Python for data pipelines, modelling, and deployment
- Work as an AWS generalist across core services (e.g. S3, EC2, Lambda, SageMaker, ECS/EKS)
- Own full ML project lifecycles, including deployment and iteration
- Support client-facing demos and product delivery
Should have experience of:
- Strong Python experience in production environments
- Broad, hands‑on AWS experience
- Proven delivery of end‑to‑end machine learning projects
- Experience deploying and maintaining models in production
- Comfortable working across technical and non‑technical teams
Helpful to have:
- MLOps, CI/CD, or model monitoring experience
- Infrastructure as Code (e.g. Terraform, CloudFormation)
- Docker / containerisation
- Client‑facing or product‑led engineering experience
What’s in it for you:
- Salary up to £70,000
- 35 days holiday
- Great benefits package (Pension, Healthcare, Life Cover, etc)
- Fully flexible hybrid working
- Learning and development budget for further education or other learning/wellbeing initiatives
Machine Learning Engineer employer: Okta Resourcing
Contact Detail:
Okta Resourcing 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 folks in the industry, attend meetups, and connect with other Machine Learning Engineers. 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 ML projects, especially those involving Python and AWS. Having tangible examples of your work can really set you apart during interviews.
✨Tip Number 3
Practice makes perfect! Prepare for technical interviews by brushing up on your Python coding skills and understanding ML concepts. Mock interviews with friends or using online platforms can help you feel more confident.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing applications directly from candidates who are excited about joining us. Tailor your application to highlight your experience with end-to-end ML projects and client-facing roles.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your Python skills and AWS experience, and don’t forget to mention any end-to-end ML projects you've worked on. We want to see how your background fits with what we’re looking for!
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 experience aligns with our needs. Be sure to mention specific projects or achievements that demonstrate your skills.
Showcase Your Projects: If you’ve got a portfolio of projects, make sure to include it! We love seeing real-world applications of your skills. Whether it’s a GitHub repo or a personal website, show us what you can do with ML solutions and Python.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status. Plus, we love seeing candidates who take the initiative to apply directly!
How to prepare for a job interview at Okta Resourcing
✨Know Your ML Stuff
Make sure you brush up on your machine learning concepts and techniques. Be ready to discuss your past projects in detail, especially those that involved end-to-end delivery. Highlight your experience with Python and AWS, as these are crucial for the role.
✨Showcase Your Problem-Solving Skills
Prepare to tackle hypothetical scenarios during the interview. Think about how you would approach designing and deploying an ML solution from scratch. This will demonstrate your hands-on experience and ability to think critically under pressure.
✨Communicate Clearly
Since this role involves working with both technical and non-technical teams, practice explaining complex concepts in simple terms. Being able to articulate your ideas clearly will show that you can bridge the gap between different stakeholders.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions! Inquire about the team’s current projects, challenges they face, or their approach to MLOps. This shows your genuine interest in the role and helps you assess if it’s the right fit for you.