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
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 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 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 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 AWS, Python, and MLOps. This gives you a chance to demonstrate your hands-on experience and problem-solving abilities to potential employers.
✨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 detail. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Keep an eye on our job listings and make sure your application stands out by tailoring it to the role.
We think you need these skills to ace AWS Engineer 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 like AWS, Azure, or GCP, and don’t forget to mention your production-grade Python skills!
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!
Showcase Your Projects:If you've worked on any relevant projects, whether in a professional setting or as personal endeavours, make sure to include them. We love seeing real-world applications of your skills, especially in building scalable ML systems.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re genuinely interested in joining our team at StudySmarter!
How to prepare for a job interview at Gravitas Recruitment Group (Global) Ltd
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python, AWS, and DevOps practices. Brush up on your knowledge of Docker and CI/CD processes, as these will likely come up during technical discussions.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've tackled complex problems in previous roles. Think about how you designed and implemented ML pipelines or optimised existing systems, as this will demonstrate your hands-on experience and ability to deliver results.
✨Engage with Emerging Technologies
Express your curiosity about new trends in AI and MLOps. Be ready to share your thoughts on recent advancements or tools you've explored. This shows your enthusiasm for the field and your commitment to staying updated with industry developments.
✨Be Ready for Agile Discussions
Since the role involves working in agile teams, be prepared to talk about your experiences in agile environments. Discuss your participation in sprint planning, retrospectives, and code reviews, highlighting how you contribute to team dynamics and project success.
