At a Glance
- Tasks: Build and deploy production-grade ML systems in a collaborative environment.
- Company: Fast-growing AI & Machine Learning consultancy with a technical culture.
- Benefits: Competitive salary, bonus, EMI share scheme, and hybrid working.
- Other info: Clear progression opportunities and a supportive, low-ego team.
- Why this job: Join a team making real impact on high-stakes AI projects.
- Qualifications: Strong Python skills and experience in deploying ML models.
The predicted salary is between 45000 - 80000 € per year.
A fast-growing AI & Machine Learning consultancy is looking to hire multiple MLOps Engineers as they scale their technical team following continued growth across major public sector and enterprise projects. This is an opportunity to join a highly technical engineering environment focused on building real-world production ML applications, not proof-of-concepts or internal experimentation. You’ll work alongside a team of experienced ML Engineers, Software Engineers and Technical Leads delivering scalable AI systems for customers operating in complex, high-impact environments.
What you’ll be doing:
- Building and deploying production-grade ML systems
- Working across cloud infrastructure, automation and model serving
- Designing scalable MLOps pipelines and infrastructure
- Collaborating closely with engineers, data scientists and clients
- Contributing to architecture decisions and engineering best practices
- Supporting the deployment and monitoring of ML applications in production
Tech environment includes:
- Python
- AWS / Azure / GCP
- Kubernetes & Docker
- FastAPI
- Infrastructure as Code
- CI/CD pipelines
- ML frameworks such as PyTorch / TensorFlow
What they’re looking for:
- Strong Python engineering experience
- Experience deploying ML models into production
- Cloud and containerisation experience
- Excellent communication skills
- Someone who enjoys solving complex technical problems collaboratively
- Consultancy mindset / comfortable working across multiple projects
Nice to have:
- Experience in MLOps or ML platforms
- Experience in consultancy environments
- Exposure to public sector or regulated environments
- Strong academic background (Master's / PhD beneficial)
What’s on offer:
- High-performing, deeply technical engineering culture
- Opportunity to work on genuinely impactful AI projects
- Clear progression opportunities as the company scales
- EMI share scheme with strong long-term upside
- Hybrid working (Manchester office)
- Collaborative, low-ego team environment
If you’re interested in hearing more, apply directly or reach out for a confidential conversation.
Senior MLOps Engineer employer: Hiiya
Join a fast-growing AI & Machine Learning consultancy in Manchester, where you'll be part of a high-performing, deeply technical engineering culture. With opportunities to work on impactful projects and clear pathways for career progression, this role offers a collaborative, low-ego environment that values your contributions and fosters growth. Enjoy the benefits of hybrid working and an EMI share scheme that provides strong long-term upside as the company continues to scale.
StudySmarter Expert Advice🤫
We think this is how you could land Senior MLOps Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry on LinkedIn or at local meetups. We can’t stress enough how valuable personal connections can be when it comes to landing that MLOps Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving ML systems and cloud infrastructure. This gives potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and MLOps knowledge. We recommend practicing coding challenges and discussing your past experiences with deploying ML models in production.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love hearing from passionate candidates who are eager to join our collaborative team.
We think you need these skills to ace Senior MLOps Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Senior MLOps Engineer role. Highlight your Python engineering experience and any cloud or containerisation work you've done. We want to see how you can contribute to our team!
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 consultancy mindset. Let us know what excites you about working on impactful AI projects.
Showcase Your Problem-Solving Skills:In your application, don’t just list your skills—give us examples of how you've tackled complex technical problems in the past. We love seeing how you collaborate with others to find solutions, so share those stories!
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and get back to you quickly. We can’t wait to hear from you!
How to prepare for a job interview at Hiiya
✨Know Your Tech Inside Out
Make sure you’re well-versed in the tech stack mentioned in the job description. Brush up on Python, cloud platforms like AWS or Azure, and containerisation tools like Docker and Kubernetes. Being able to discuss your hands-on experience with these technologies will show that you're ready to hit the ground running.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've tackled complex technical problems. Think about challenges you've faced in deploying ML models or designing MLOps pipelines. This will demonstrate your consultancy mindset and ability to work collaboratively across projects.
✨Communicate Clearly and Confidently
Since excellent communication skills are a must-have, practice explaining your past projects and technical concepts in a clear and concise manner. Remember, you’ll be collaborating closely with engineers and clients, so showing that you can articulate your thoughts effectively is key.
✨Understand the Company Culture
Research the company’s engineering culture and values. Be prepared to discuss how you align with their focus on building impactful AI systems and your interest in contributing to architecture decisions. This shows that you’re not just looking for a job, but a place where you can grow and make a difference.
