At a Glance
- Tasks: Build and deliver scalable machine learning systems for exciting client projects.
- Company: Fast-growing tech consultancy at the forefront of AI and modern engineering.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Dynamic environment with a focus on emerging technologies and career advancement.
- Why this job: Join a collaborative team and make a real impact in the world of MLOps.
- Qualifications: Experience in Python, cloud platforms, and DevOps practices required.
The predicted salary is between 60000 - 80000 £ per year.
Our client is a fast-growing, specialist technology consultancy focused on helping organisations successfully deploy and scale machine learning solutions in production. Operating at the forefront of AI and modern engineering, they partner with a wide range of clients to turn cutting-edge research into real-world impact.
As an MLOps Engineer, you will play a key role in delivering production-ready machine learning systems within cross-functional engineering teams. Working across multiple client engagements, you’ll contribute to the design, build, and deployment of scalable ML solutions. This is a hands-on role suited to engineers who enjoy solving complex problems, working directly with stakeholders, and staying close to emerging technologies within AI and MLOps.
You’ll be involved throughout the full delivery lifecycle, from early-stage discovery through to deployment and optimisation, while contributing to best practices and engineering excellence.
- Strong experience writing production-grade Python
- Hands-on experience with cloud platforms (AWS, Azure, or GCP)
- Solid understanding of DevOps practices, CI/CD, and infrastructure-as-code
- Experience with Docker, Git, and Linux-based environments
- Familiarity with machine learning frameworks
- Experience working in agile delivery teams
- Curiosity and enthusiasm for emerging technologies within AI and MLOps
Key Responsibilities:
- Build and deliver scalable machine learning systems for a variety of client projects
- Design and implement robust ML pipelines and supporting infrastructure
- Contribute to engineering best practices, code quality, and documentation
- Participate in agile ceremonies including sprint planning, retrospectives, and code reviews
Additional Requirements:
- Right to work in the UK and ability to obtain security clearance
- Background in software engineering, data, or a related technical discipline
- Experience working within project-based or client-facing environments is beneficial
- Ability to work in a hybrid model with regular on-site collaboration
If you're looking to work at the cutting edge of MLOps and AI, while contributing to high-impact projects in a collaborative and forward-thinking environment, we’d love to hear from you.
AWS Engineer with DevOps in Manchester employer: Gravitas Recruitment Group (Global) Ltd
Join a dynamic and innovative technology consultancy that prioritises employee growth and collaboration. With a strong focus on cutting-edge AI and MLOps, you'll have the opportunity to work on impactful projects while enjoying a supportive work culture that encourages continuous learning and development. Located in a vibrant area, our hybrid working model fosters flexibility and regular on-site collaboration, making it an excellent place for engineers eager to make a difference.
Contact Details:
Gravitas Recruitment Group (Global) Ltd Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land AWS Engineer with DevOps in Manchester
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential employers on LinkedIn. We all know that sometimes it’s not just what you know, but who you know!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving AWS, DevOps, or machine learning. We want to see what you can do, so make it easy for us to find your best work.
✨Tip Number 3
Prepare for interviews by practising common technical questions and scenarios related to MLOps and cloud platforms. We recommend doing mock interviews with friends or using online resources to boost your confidence.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love hearing from candidates who are genuinely interested in joining our team.
We think you need these skills to ace AWS Engineer with DevOps in Manchester
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the MLOps Engineer role. Highlight your hands-on experience with cloud platforms and any relevant projects you've worked on. We want to see how you can contribute to our mission!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and MLOps, and how your background in software engineering makes you a great fit for our team. Keep it engaging and personal – we love to see your personality!
Showcase Your Projects:If you've worked on any production-grade Python projects or have experience with Docker and CI/CD, make sure to mention them. We’re keen to see real examples of your work and how you’ve tackled complex problems in the past.
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, it shows you’re serious about joining our team!
How to prepare for a job interview at Gravitas Recruitment Group (Global) Ltd
✨Know Your Tech Inside Out
Make sure you brush up on your Python skills and get comfortable with AWS, Azure, or GCP. Be ready to discuss your hands-on experience with cloud platforms and how you've used them in past projects. This will show that you're not just familiar with the tools, but that you can actually apply them effectively.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of complex problems you've solved in previous roles. Think about how you designed and implemented ML pipelines or contributed to DevOps practices. This will demonstrate your ability to think critically and work through challenges, which is key for an MLOps Engineer.
✨Emphasise Collaboration and Agile Experience
Since this role involves working in cross-functional teams, be ready to talk about your experience in agile environments. Highlight any participation in sprint planning, retrospectives, or code reviews. This shows that you value teamwork and understand the importance of collaboration in delivering successful projects.
✨Stay Curious About Emerging Technologies
Express your enthusiasm for AI and MLOps by discussing any recent trends or technologies you've been following. This could be new machine learning frameworks or advancements in infrastructure-as-code. Showing that you're proactive about learning will impress interviewers and align with their forward-thinking approach.
