At a Glance
- Tasks: Build and maintain scalable machine learning solutions on Microsoft Azure.
- Company: Join a dynamic team in a growing tech environment.
- Benefits: Competitive daily rate, hands-on experience, and collaborative work culture.
- Other info: Onsite role with opportunities for professional growth and skill development.
- Why this job: Make an impact by deploying cutting-edge ML solutions in a fast-paced setting.
- Qualifications: Experience with Azure MLOps, CI/CD pipelines, and containerization.
The predicted salary is between 63000 - 77000 £ per year.
Location: Wokingham, UK
Employment Type: Contract
Duration: 6 months
Work Mode: Office-based (5 days per week)
Rate: Up to £450/day
About the Role
We are looking for an experienced Azure MLOps Engineer to join a growing team responsible for building, deploying, and maintaining scalable machine learning solutions on Microsoft Azure. You will work closely with Data Scientists, DevOps Engineers, Architects, and Software Developers to deliver reliable, secure, and automated MLOps platforms supporting large-scale data processing and production ML workloads.
Key Responsibilities
- Deploy machine learning models into Azure production environments.
- Design, implement, and maintain Azure MLOps infrastructure.
- Build and manage CI/CD pipelines for machine learning solutions using Azure DevOps.
- Containerize applications and ML models using Docker.
- Monitor model performance, health, and reliability in production.
- Implement logging, monitoring, and alerting solutions.
- Optimize infrastructure for scalability, performance, and cost efficiency.
- Implement automated deployment and scaling strategies.
- Manage Azure cloud resources supporting ML workloads.
- Ensure security, governance, and compliance with data protection standards.
- Manage data pipelines, storage, versioning, and lineage.
- Collaborate with cross-functional teams to support end-to-end ML life cycle management.
- Troubleshoot production issues and continuously improve platform performance.
- Maintain technical documentation and communicate effectively with both technical and non-technical stakeholders.
Required Skills
Azure MLOps Engineer - Inside IR35 - Onsite employer: Hamilton Barnes
Hamilton Barnes is an exceptional employer, offering a dynamic work environment in London where innovation meets opportunity. With competitive salaries, night shift allowances, and a strong focus on employee development through ongoing training, we empower our Field Service Engineers to advance their careers while enjoying a supportive team culture. Join us to be part of a growing engineering team that values your skills and fosters professional growth.
StudySmarter Expert Advice🤫
We think this is how you could land Azure MLOps Engineer - Inside IR35 - Onsite
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We think you need these skills to ace Azure MLOps Engineer - Inside IR35 - Onsite
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at Hamilton Barnes, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to Hamilton Barnes, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab Hamilton Barnes’s attention and show the tangible impact of your work.
How to prepare for a job interview at Hamilton Barnes
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at Hamilton Barnes.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at Hamilton Barnes.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at Hamilton Barnes.
