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- Tasks: Lead the AI production lifecycle and build high-performance Computer Vision systems.
- Company: Innovative AI company focused on advanced visual intelligence technology.
- Benefits: Strong engineering culture, high technical ownership, and real-world impact.
- Other info: Opportunity to mentor and grow international AI/ML teams in an Agile setting.
- Why this job: Shape the future of AI while tackling challenging problems in a dynamic environment.
- Qualifications: Proven experience in ML or Computer Vision, strong Python and C++ skills.
The predicted salary is between 80000 - 100000 £ per year.
I’m currently partnering with a highly innovative AI company building advanced Computer Vision and visual intelligence technology deployed at global scale.
The company is looking for someone who can take ownership of the entire AI production lifecycle - from raw data collection and training pipelines through to robust, production-ready models operating in demanding environments.
The role is ideal for someone who combines deep technical expertise with a hands-on approach to engineering and leadership.
You will lead the design and evolution of the company’s AI production pipeline, covering data ingestion, organisation, annotation strategy, model training, validation, optimisation, deployment, and monitoring.
The focus is on building industrial-grade Computer Vision systems that perform reliably outside the lab - with real constraints around latency, scalability, reliability, and throughput.
You’ll work closely with Engineering, Product, and AI teams to ensure research and technical innovation translate directly into commercial impact.
You’ll have the autonomy to help shape the structure, standards, and direction of the AI/ML function, while hiring and developing a high-performing international team.
- Own and scale the end-to-end AI/ML production lifecycle
- Build high-performance Computer Vision systems for production deployment
- Define standards across MLOps, model quality, deployment, monitoring, and engineering best practice
- Improve the speed and efficiency of taking models from raw data to production
- Work cross-functionally with Product and Engineering teams on long-term technical strategy
- Hire, mentor, and grow AI/ML engineering teams across multiple locations
- Establish scalable team structures, workflows, and delivery processes within an Agile environment
Proven track record delivering ML or Computer Vision products into production at scale.
Strong expertise across modern Computer Vision techniques and deep learning architectures.
Excellent Python and C++ engineering skills.
Experience optimising training and inference pipelines for real-world deployment.
Strong systems and engineering mindset alongside deep ML knowledge.
MSc or PhD in Computer Science, Machine Learning, or a related field preferred.
The company offers a strong engineering culture, high levels of technical ownership, and the opportunity to work on difficult AI problems with direct real-world impact.
AWS Principal Engineer in Manchester employer: NearTech Search
Contact Detail:
NearTech Search Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AWS Principal 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 related to AI/ML and Computer Vision. This gives you a chance to demonstrate your expertise beyond just a CV.
✨Tip Number 3
Prepare for interviews by brushing up on technical questions and real-world problem-solving scenarios. Practice explaining your thought process clearly, as communication is key in collaborative environments.
✨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 seeing candidates who are proactive about their job search.
We think you need these skills to ace AWS Principal Engineer in Manchester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the role of Principal AI/ML Engineer. Highlight your expertise in Computer Vision and any relevant projects you've led, as this will show us you’re a great fit for our innovative team.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you're passionate about AI and how your hands-on approach can help shape our AI production pipeline. Be specific about your achievements and how they relate to the job description.
Showcase Your Technical Skills: Don’t hold back on showcasing your technical prowess! Mention your experience with Python, C++, and any modern Computer Vision techniques. We want to see how you’ve optimised training and inference pipelines in real-world scenarios.
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, we love seeing candidates who take that extra step!
How to prepare for a job interview at NearTech Search
✨Know Your Stuff
Make sure you brush up on your knowledge of modern Computer Vision techniques and deep learning architectures. Be ready to discuss specific projects you've worked on, especially those that involved taking ML products into production at scale.
✨Show Your Leadership Skills
Since this role involves mentoring and growing teams, be prepared to share examples of how you've led teams in the past. Talk about your approach to building high-performing teams and how you’ve established workflows in an Agile environment.
✨Demonstrate Problem-Solving Abilities
Expect to face technical challenges during the interview. Think through how you would optimise training and inference pipelines for real-world deployment. Show them your systems mindset by discussing how you tackle complex engineering problems.
✨Align with Their Vision
Research the company’s AI production lifecycle and their focus on commercial impact. Be ready to discuss how your experience aligns with their goals and how you can contribute to shaping the structure and standards of their AI/ML function.