At a Glance
- Tasks: Automate ML model deployment and integrate AI systems for real-world impact.
- Company: Join a forward-thinking organisation leading in AI and machine learning innovation.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Other info: Flexible location with multiple experience levels welcomed.
- Why this job: Be at the forefront of AI technology and make a difference in the banking sector.
- Qualifications: Experience in ML/AI engineering and strong skills in model deployment and integration.
The predicted salary is between 50000 - 70000 £ per year.
We’re Hiring on Behalf of Our Client: ML & AI Engineers. Our client, a forward-thinking organization investing heavily in AI and machine learning innovation, is looking to hire ML & AI Engineers across multiple experience levels. If you’re passionate about deploying scalable AI systems and working on cutting-edge technologies, this could be your next move.
Role Overview
As an ML & AI Engineer, you will be responsible for automating model deployment, managing version control, and ensuring production-ready AI systems. You’ll also play a key role in integrating AI/LLM agents with strong observability and rollback mechanisms.
Location: Leeds/Manchester
Client: IT
End Client: Banking domain
Work Mode: Hybrid
Contract: Inside IR 35
Salary: Market Standards
Key Responsibilities
- Automate ML model deployment workflows
- Manage model versioning and release processes
- Monitor inference cost, latency, and model drift
- Safely integrate AI/LLM agents into production systems
- Implement observability, alerting, and rollback mechanisms
Experience Levels
We’re hiring across multiple seniority levels:
- Senior Developer: 3–6 years (ML/AI Engineering)
- Lead Engineer: 7–9 years (ML/AI Engineering)
- Architect: 10+ years (ML/AI Engineering)
Required Skills
- Model deployment automation
- Model version control
- Monitoring (cost, latency, drift)
- Production integration of AI/LLM agents
- Observability & rollback systems
Preferred Skills
- Experience with containerized environments (Docker/Kubernetes)
- Familiarity with CI/CD pipelines for ML (MLOps)
Education
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
Location
Flexible / Open (depending on project requirements)
Employment Type
Full-time
Why Apply?
This is a fantastic opportunity to work with a client at the forefront of AI innovation, building scalable, production-grade systems that make a real impact. Interested? Apply now or message me directly to learn more. Referrals are welcome!
ML & AI -Engineers/Architect/Lead in England employer: KBC Technologies Group
Join a pioneering organisation in Leeds/Manchester that is at the forefront of AI and machine learning innovation. With a strong commitment to employee growth, a hybrid work model, and a culture that fosters creativity and collaboration, this company offers a unique opportunity to work on impactful projects while enjoying competitive market-standard salaries and a supportive environment for professional development.
StudySmarter Expert Advice🤫
We think this is how you could land ML & AI -Engineers/Architect/Lead in England
✨Tip Number 1
Network like a pro! Reach out to folks 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 related to ML and AI. This gives you a chance to demonstrate your expertise and passion for the field beyond just your CV.
✨Tip Number 3
Prepare for interviews by brushing up on common ML and AI questions. Practice explaining your past projects and how you tackled challenges. Confidence is key, so make sure you can articulate your thought process clearly.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always looking for passionate individuals ready to dive into the world of AI and machine learning.
We think you need these skills to ace ML & AI -Engineers/Architect/Lead in England
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the ML & AI Engineer role. Highlight your experience in model deployment automation and any relevant projects you've worked on.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about AI and machine learning. Share specific examples of how you've integrated AI systems in the past and what excites you about this opportunity.
Showcase Your Technical Skills:Don’t forget to mention your familiarity with tools like Docker, Kubernetes, and CI/CD pipelines. We want to see how you can contribute to our client's innovative projects right from the get-go!
Apply Through Our Website:For the best chance of getting noticed, apply directly through our website. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at KBC Technologies Group
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, like model deployment automation and version control. Brush up on your knowledge of AI/LLM agents and how they integrate into production systems, as this will likely come up during the interview.
✨Showcase Your Projects
Prepare to discuss specific projects where you've automated ML workflows or managed model versioning. Be ready to explain the challenges you faced and how you overcame them, as this demonstrates your hands-on experience and problem-solving skills.
✨Understand the Business Context
Since the role is within the banking domain, it’s beneficial to understand how AI and machine learning can impact financial services. Research current trends in AI applications in banking to show that you’re not just a techie but also understand the business side of things.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s AI initiatives and their approach to model monitoring and observability. This shows your genuine interest in the role and helps you gauge if the company aligns with your career goals.
