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- Tasks: Design and build MLOps platforms for real-world machine learning applications.
- Company: Join a consultancy-led team delivering cutting-edge ML solutions.
- Benefits: Competitive day rate, remote work, and opportunities for travel.
- Why this job: Make a tangible impact by taking ML systems from experimentation to production.
- Qualifications: Strong MLOps experience and hands-on expertise with MLflow required.
- Other info: Dynamic role with a focus on collaboration and best practices in ML.
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 Bristol employer: Inara
Contact Detail:
Inara Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer in Bristol
✨Tip Number 1
Network like a pro! Reach out to your connections in the MLOps space and let them know you're on the hunt for a role. Attend meetups or webinars related to machine learning and engage with others in the field. You never know who might have a lead on that perfect contract!
✨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 and how you can help them scale their ML systems.
✨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 hear about your hands-on experience, so come armed with examples!
✨Tip Number 4
Don't forget to apply through our website! We’ve got loads of opportunities that might just be the right fit for you. Plus, applying directly helps us get to know you better and match you with roles that suit your skills and experience.
We think you need these skills to ace Machine Learning Engineer in Bristol
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!
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 cover letter, keep it clear and to the point. Explain why you're a great fit for this role and how your experience aligns with our needs. We appreciate straightforward communication!
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to see what you bring to the table!
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 your hands-on experience with these tools and how you've implemented them in real-world scenarios. Prepare specific examples of projects where you’ve taken models from experimentation to production.
✨Showcase Your CI/CD Skills
Since this role involves putting robust CI/CD pipelines in place for ML workflows, be prepared to talk about your experience with CI/CD in ML contexts. Highlight any specific tools or frameworks you've used, and be ready to explain how you’ve ensured smooth deployments and monitoring of ML models.
✨Collaborate Like a Pro
This position requires close collaboration with Data Scientists, so think of examples where you’ve successfully partnered with others to move models into production. Discuss how you’ve facilitated communication and ensured that everyone is on the same page regarding model governance and monitoring.
✨Prepare for Technical Questions
Expect technical questions that dive deep into your experience with cloud platforms, Docker, Kubernetes, and Infrastructure as Code. Brush up on your Python skills too, as you may need to demonstrate your ability to work with Python-based ML workflows. Practice explaining complex concepts in a simple way to show your understanding.