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- Tasks: Build and optimise ML platforms using Python, AWS, and GCP.
- Company: Dynamic tech company with a focus on innovation and collaboration.
- Benefits: Competitive daily rate of £600–£700 and flexible contract opportunities.
- Why this job: Join a cutting-edge team and make an impact in the ML space.
- Qualifications: Experience in Python, MLOps, and cloud platforms like AWS and GCP.
- Other info: Work on-site in vibrant Amsterdam or London with great career growth.
The predicted salary is between 120000 - 140000 £ per year.
This role is for a Machine Learning Engineer with a contract length of multiple opportunities, offering £600–£700/day.
Key skills include:
- Python
- MLOps
- AWS
- GCP
- Terraform
Work location is on-site in Amsterdam or London.
Responsibilities:
- Internal ML platform built on EKS
- Standardised stack: EKS, CKD, GitHub Actions, CI/CD, Terraform
- Heavy Python layer for automation and ML workflows
- Operate across AWS & GCP (cross-cloud experience is a big plus)
- MLOps focus: model deployment, monitoring, and scaling
- Collaborate with ML teams to unify infrastructure and pipelines
Role Details:
- Location: Amsterdam or London
- Rate: £600–£700/day depending on location
Machine Learning Engineer employer: Data Freelance Hub
Contact Detail:
Data Freelance Hub 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 your connections in the machine learning field, especially those who work with AWS or GCP. 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 Python projects, MLOps implementations, and any Terraform scripts you've written. This will give potential employers a taste of what you can do before they even meet you.
✨Tip Number 3
Prepare for technical interviews by brushing up on your ML concepts and coding skills. Practice common algorithms and deployment strategies, so you can confidently discuss your experience with model monitoring and scaling.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got a community-driven approach that connects you directly with hiring managers, making it easier for us to find the right fit for you.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with Python, MLOps, AWS, GCP, and Terraform in your application. We want to see how your skills align with the role, so don’t hold back!
Tailor Your Application: Customise your application to reflect the job description. Mention specific projects or experiences that relate to building ML platforms or working with CI/CD pipelines. This helps us see you as a perfect fit!
Be Clear and Concise: Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon unless it’s relevant. Make it easy for us to understand your qualifications and experiences.
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 this exciting opportunity!
How to prepare for a job interview at Data Freelance Hub
✨Know Your Tech Stack
Make sure you’re well-versed in Python, AWS, GCP, and Terraform. Brush up on your knowledge of EKS and CI/CD processes, as these are crucial for the role. Being able to discuss how you've used these technologies in past projects will really impress the interviewers.
✨Showcase Your MLOps Experience
Since this role has a strong MLOps focus, be prepared to talk about your experience with model deployment, monitoring, and scaling. Share specific examples of how you've collaborated with teams to unify infrastructure and pipelines, as this will demonstrate your ability to work effectively in a team setting.
✨Prepare for Scenario Questions
Expect scenario-based questions that test your problem-solving skills. Think about challenges you've faced in previous roles and how you overcame them, especially in cross-cloud environments. This will show your adaptability and technical prowess.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions! Inquire about the internal ML platform and how the team collaborates on projects. This not only shows your interest in the role but also helps you gauge if the company culture aligns with your values.
