At a Glance
- Tasks: Tackle real-world ML challenges to boost business growth and optimise payment systems.
- Company: Join a dynamic tech company focused on innovation and collaboration.
- Benefits: Competitive pay, remote work flexibility, and a supportive team environment.
- Other info: Exciting opportunity for career growth in a collaborative team of engineers.
- Why this job: Make a tangible impact in a fast-paced, agile setting with cutting-edge technology.
- Qualifications: 5+ years in production ML systems and strong TensorFlow skills required.
The predicted salary is between 37875 - 51000 £ per year.
Location: England, UK - Remote
Duration: 6-Month Contract with potential extension
Payrate: £525 - £715 per day Inside IR35
About the Role
We are looking for a seasoned Machine Learning Engineer to join our Client Subscription Mission for a 6-month contract. In this role, you will bypass recommendation engines and generative AI to dive into classic production ML problems directly impacting business growth (MAUs and Subscriber metrics). Specifically, you will anchor their Payments Optimization efforts - improving payment retry mechanisms, reducing failures, and collaborating on network token optimization within their commerce domain.
You'll step into an agile, highly collaborative environment of 5-6 tightly-knit engineers with daily stand-ups and a strong peer-support structure.
What We Are Looking For
- Experience: Minimum 5+ years of proven industry experience working on production-level ML systems. (Note: This is a system-heavy deployment role, not a research or prototyping position).
- The Technical Stack: Strong proficiency in TensorFlow is strictly required. Experience with Kubeflow is a massive plus.
- Lifecycle Ownership: Complete comfort handling the end-to-end ML lifecycle: prototyping, building robust data pipelines, monitoring, and executing drift detection.
- Soft Skills: A collaborative team player who can easily interface with business stakeholders, translate business needs into technical objectives, and provide clear technical direction.
Preferred Backgrounds
While a direct background in fintech or payment processing is a great nice-to-have, it is not a requirement. They value engineers who have solved complex data problems at scale. Experience working in high-growth, large-scale tech companies or scale-ups is highly regarded.
This is an urgent role where Hiring Manager is looking to shortlist for an interview urgently. If you are interested then please apply with a copy of your CV or send your CV to khushboo.pandey@randstad.co.uk.
Randstad Technologies is acting as an Employment Business in relation to this vacancy.
Machine Learning Engineer in London employer: Randstad Technologies Recruitment
Join a forward-thinking company that values innovation and collaboration, offering a dynamic remote work environment for Machine Learning Engineers. With a strong focus on employee growth, you will have the opportunity to tackle impactful projects in payment optimization while being supported by a close-knit team of skilled professionals. Enjoy competitive pay rates and the flexibility of working from anywhere in England, making this an ideal place for those seeking meaningful and rewarding employment.
Contact Details:
Randstad Technologies Recruitment Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, especially those who might know about opportunities in machine learning. A friendly chat can sometimes lead to a job offer before it even gets posted!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best machine learning projects. Whether it's a GitHub repo or a personal website, having tangible examples of your work can really impress potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on common ML concepts and problem-solving techniques. Practice explaining your past projects and how you tackled challenges. Confidence and clarity can make all the difference!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of exciting roles waiting for talented engineers like you. Plus, applying directly can sometimes give you an edge over other candidates.
We think you need these skills to ace Machine Learning Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your experience with production-level ML systems and any specific projects that relate to payment optimization or data pipelines.
Showcase Your Skills:Don’t forget to showcase your proficiency in TensorFlow and any experience with Kubeflow. We want to see how you’ve handled the end-to-end ML lifecycle, so include relevant examples!
Be Clear and Concise:When writing your application, keep it clear and concise. Use bullet points where possible to make it easy for us to read through your qualifications and experiences quickly.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any updates!
How to prepare for a job interview at Randstad Technologies Recruitment
✨Know Your ML Stuff
Make sure you brush up on your machine learning fundamentals, especially around production-level systems. Be ready to discuss your experience with TensorFlow and any projects where you've tackled classic ML problems. This is your chance to show off your technical prowess!
✨Showcase Your Collaboration Skills
Since this role involves working closely with a tight-knit team, be prepared to share examples of how you've successfully collaborated in the past. Highlight situations where you translated business needs into technical objectives, as this will demonstrate your ability to interface with stakeholders effectively.
✨Understand the Business Impact
Familiarise yourself with how machine learning can drive business growth, particularly in areas like payment optimisation. Be ready to discuss how your work has previously impacted metrics like MAUs or subscriber growth, as this will resonate well with the hiring manager.
✨Prepare for Technical Questions
Expect some deep dives into your technical expertise during the interview. Prepare to discuss the end-to-end ML lifecycle, including data pipelines and drift detection. Practising common technical questions can help you feel more confident and articulate your thought process clearly.
