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- Tasks: Design and build MLOps platforms, ensuring smooth deployment of ML models.
- Company: Join a consultancy-led team delivering cutting-edge machine learning solutions.
- Benefits: Competitive day rate, remote work, and opportunities for professional growth.
- Why this job: Make a real impact by transforming ML systems into reliable production environments.
- Qualifications: Strong MLOps experience and hands-on expertise with MLflow are essential.
- Other info: Dynamic role with potential for exciting projects and career advancement.
Contract Machine Learning Engineer | MLflow | Databricks | Production ML
Duration: Initially 3 months
Day rate: £500 - £550, Inside IR35
Workplace: Remote, with occasional travel to client-site
Inara are supporting a consultancy-led team delivering production-grade machine learning platforms for a range of end clients, and they’re looking for a senior, hands-on Contract MLOps Engineer to help take ML systems from experimentation into reliable, scalable production. This role is firmly focused on ML enablement and platform engineering rather than model research. You’ll be the person ensuring models can be trained, tracked, deployed, governed, and monitored properly in real-world environments.
What you’ll be doing:
- Designing and building end-to-end MLOps platforms that support the full ML lifecycle
- Implementing and operating MLflow for experiment tracking, model registry, and versioning
- Enabling production deployments of ML models (batch and/or real-time)
- Putting robust CI/CD pipelines in place for ML workflows
- Partnering closely with Data Scientists to move models from notebooks into production
- Establishing best practices around model governance, monitoring, retraining, and environments
- Integrating ML platforms with Databricks and cloud-native services
What we’re looking for:
- Strong, real-world MLOps experience (this is not a theoretical role)
- Deep hands-on MLflow experience — this is essential
- Proven track record of productionising ML models across multiple client or project environments
- Background in one or more of:
- MLOps / ML Engineering
- DevOps with ML platforms
- Data Science with a strong production focus
- MLflow (expert-level)
- Databricks
- Cloud platforms (AWS preferred; SageMaker exposure a bonus)
- CI/CD for ML workloads
- Docker and Kubernetes
- Infrastructure as Code (Terraform or similar)
- Python-based ML workflows
Machine Learning Engineer in Edinburgh employer: Inara
Contact Detail:
Inara Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer in Edinburgh
✨Tip Number 1
Network like a pro! Reach out to your connections in the MLOps community, attend meetups, and engage in online forums. 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 MLOps projects, especially those involving MLflow and Databricks. This will give potential employers a clear view of what you can bring to the table.
✨Tip Number 3
Prepare for technical interviews by brushing up on your hands-on experience with CI/CD pipelines and cloud platforms. Be ready to discuss how you've implemented these in real-world scenarios, as this is what they'll be looking for.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to get noticed by hiring managers who are keen on finding talent like yours.
We think you need these skills to ace Machine Learning Engineer in Edinburgh
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your hands-on experience with MLflow and any projects where you've taken models from experimentation to production. We want to see how your skills match 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 MLOps and how your background aligns with our needs. Don't forget to mention your experience with Databricks and cloud platforms, as these are key for us.
Showcase Your Projects: If you've worked on relevant projects, make sure to include them in your application. We love seeing real-world examples of your work, especially those that demonstrate your ability to implement CI/CD pipelines and manage ML workflows effectively.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get the best chance to showcase your skills directly to our team!
How to prepare for a job interview at Inara
✨Know Your MLOps Inside Out
Make sure you brush up on your MLOps knowledge, especially around MLflow and Databricks. Be ready to discuss specific projects where you've implemented these tools, as real-world experience is key for this role.
✨Showcase Your CI/CD Skills
Prepare to talk about how you've set up CI/CD pipelines for ML workflows in the past. Have examples ready that demonstrate your ability to automate and streamline the deployment process, as this will be crucial for the position.
✨Collaborate Like a Pro
Since you'll be partnering with Data Scientists, think of examples where you've successfully collaborated with cross-functional teams. Highlight how you’ve helped move models from notebooks into production and the impact it had on the project.
✨Be Ready for Technical Questions
Expect some deep technical questions during the interview. Brush up on your knowledge of Docker, Kubernetes, and Infrastructure as Code. Being able to explain your thought process and decisions in past projects will impress the interviewers.