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
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, DevOps, Machine Learning in Manchester employer: Gravitas Recruitment Group (Global) Ltd
Join a dynamic and innovative technology consultancy that prioritises employee growth and collaboration in the rapidly evolving field of machine learning. With a strong focus on cutting-edge AI solutions, our company fosters a culture of continuous learning and hands-on problem-solving, offering opportunities to work on impactful projects with diverse clients. Enjoy a flexible hybrid working model, competitive benefits, and the chance to be at the forefront of technological advancements in a supportive environment.
Contact Details:
Gravitas Recruitment Group (Global) Ltd Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Aws Engineer, DevOps, Machine Learning 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. The more you engage, the better your chances of landing that MLOps Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, AWS, or machine learning. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with CI/CD, Docker, and agile methodologies. Practice common interview questions to boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! We have multiple positions available, and applying directly can sometimes give you a leg up. Plus, it’s a great way to show your enthusiasm for working with us!
We think you need these skills to ace Aws Engineer, DevOps, Machine Learning 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 Python, cloud platforms, and DevOps practices to catch our eye!
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. We love seeing your enthusiasm shine through!
Showcase Your Problem-Solving Skills:In your application, mention instances where you've tackled complex problems in engineering or machine learning. We’re looking for candidates who thrive on challenges and can demonstrate their thought process.
Apply Through Our Website:We encourage you to apply directly through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any updates from us!
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 the cloud platforms mentioned, like AWS or Azure. Be ready to discuss your hands-on experience with Docker, Git, and CI/CD practices, as these are crucial for the role.
✨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 engineering best practices, as this will demonstrate your hands-on experience and technical prowess.
✨Familiarise Yourself with Agile Methodologies
Since the role involves working in agile delivery teams, be prepared to discuss your experience with agile ceremonies like sprint planning and retrospectives. Highlight any contributions you've made during code reviews to show your collaborative spirit.
✨Express Your Curiosity for Emerging Technologies
The company values enthusiasm for AI and MLOps, so don’t hesitate to share what excites you about these fields. Discuss any recent trends or technologies you've been following, and how you see them impacting the industry.
