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 focus.
- Benefits: Competitive salary, bonus, hybrid working, and EMI share scheme.
- Other info: Opportunities for clear progression in a 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 in Manchester 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 focused on delivering impactful AI projects. With clear progression opportunities and a collaborative, low-ego team environment, this role offers the chance to work on real-world production ML applications while enjoying the benefits of hybrid working and an EMI share scheme with strong long-term upside.
StudySmarter Expert Advice🤫
We think this is how you could land Senior MLOps Engineer in Manchester
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. 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 Python, cloud infrastructure, and CI/CD pipelines. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for technical interviews by brushing up on your problem-solving skills. Practice coding challenges and be ready to discuss your past projects in detail. Remember, they want to see how you think and approach complex problems!
✨Tip Number 4
Don’t just apply anywhere—apply through our website! We’re looking for passionate individuals who want to make an impact in AI and ML. Tailor your application to highlight your consultancy mindset and collaborative spirit.
We think you need these skills to ace Senior MLOps Engineer in Manchester
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 projects. We love seeing enthusiasm and a consultancy mindset, so let that come through in your writing.
Showcase Your Projects:If you've worked on any production-grade ML systems or relevant projects, make sure to mention them! We’re interested in real-world applications, so share your experiences with deploying models and collaborating with teams.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates. Plus, we love seeing candidates who take that extra step!
How to prepare for a job interview at Hiiya
✨Know Your Tech Stack
Make sure you’re well-versed in the tech stack mentioned in the job description. Brush up on your Python skills, and be ready to discuss your experience with AWS, Azure, or GCP. Familiarity with Kubernetes, Docker, and CI/CD pipelines will definitely give you an edge.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've tackled complex technical problems. Think about how you’ve built and deployed ML systems in the past, and be ready to explain your thought process. This will demonstrate your consultancy mindset and collaborative approach.
✨Understand MLOps Fundamentals
Since this role focuses on MLOps, make sure you can articulate what MLOps means to you. Be prepared to discuss designing scalable MLOps pipelines and infrastructure, and how you’ve contributed to architecture decisions in previous roles.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the company’s projects, team dynamics, and future goals. This shows your genuine interest in the role and helps you assess if it’s the right fit for you.
