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- Tasks: Design and build MLOps platforms, ensuring smooth deployment of ML models.
- Company: Join a consultancy-led team focused on innovative 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 Birmingham employer: Inara
Contact Detail:
Inara Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer in Birmingham
✨Tip Number 1
Network like a pro! Reach out to your connections in the MLOps space, attend meetups, and engage in online forums. You never know who might have the inside scoop on a job opportunity.
✨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 taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on real-world scenarios. Be ready to discuss how you've tackled challenges in productionising ML models and implementing CI/CD pipelines. We want to see your hands-on experience!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Machine Learning Engineer in Birmingham
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 relevant projects where you've taken models from experimentation to production. We want to see how your skills match what we're looking for!
Showcase Your Projects: Include specific examples of MLOps platforms you've designed or worked on. If you've implemented CI/CD pipelines or integrated ML platforms with Databricks, let us know! Real-world examples will make your application stand out.
Be Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points for your achievements and responsibilities to make it easy for us to read. We appreciate a well-structured application that gets straight to the good stuff!
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It helps us keep track of applications and ensures you’re considered for the role. Don’t miss out on this opportunity!
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 experimentation to production, showcasing your teamwork skills.
✨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 problem-solving approach will impress the interviewers.