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 agile practices.
- Why this job: Join a collaborative team and make a real impact in the world of MLOps.
- Qualifications: Strong Python skills and experience with cloud platforms like AWS or Azure.
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
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
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 (Python) 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 allows for flexibility and regular on-site collaboration, making it an excellent place for engineers passionate about solving complex problems.
Contact Details:
Gravitas Recruitment Group (Global) Ltd Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land AWS Engineer (Python) 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 projects, especially those involving Python and cloud platforms like AWS. This gives you a chance to demonstrate your hands-on experience and problem-solving abilities.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common interview questions related to MLOps and be ready to discuss your past experiences in agile teams and client-facing roles.
✨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 candidates who are excited about working at the forefront of AI and MLOps.
We think you need these skills to ace AWS Engineer (Python) 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 production-grade Python experience and any cloud platform work you've done, as these are key for us.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about AI and MLOps. Share specific examples of projects you've worked on and how they relate to the role. This is your chance to show your enthusiasm!
Showcase Your Problem-Solving Skills:In your application, mention instances where you've tackled complex problems in engineering or machine learning. We love seeing how you approach challenges and what solutions you've implemented.
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’re considered for the role. Plus, it’s super easy!
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 any cloud platforms you've worked with, especially AWS. Be ready to discuss specific projects where you've implemented machine learning solutions, as this will show your hands-on experience.
✨Showcase Your Problem-Solving Skills
Prepare to talk about complex problems you've solved in previous roles. Use the STAR method (Situation, Task, Action, Result) to structure your answers, highlighting how you approached challenges in MLOps or software engineering.
✨Familiarise Yourself with Agile Practices
Since the role involves working in agile teams, be prepared to discuss your experience with agile methodologies. Mention any specific ceremonies you've participated in, like sprint planning or retrospectives, to demonstrate your collaborative spirit.
✨Stay Curious About Emerging Technologies
Show your enthusiasm for AI and MLOps by discussing recent trends or technologies that excite you. This not only reflects your passion but also aligns with the company's focus on cutting-edge solutions.
