Advanced Manufacturing Project Engineer (AI & Connectivity)
Integrating computer vision, applied AI, and physical-world sensing to develop novel solutions for advanced manufacturing environments.
A 14-year arc from first-line IT through to applied AI and sensing in advanced manufacturing — including 3 years in engineering environments and 1 year embedded within the AMRC.
Professional Summary
I have over 10 years of experience in information technology, connectivity, and IT service delivery, alongside 3 years working within engineering environments, including prototyping and advanced manufacturing settings, and one year embedded within the Advanced Manufacturing Research Centre (AMRC). This provides equivalent practical experience to a degree-level background. In my current role as Senior IT Technician – Projects, I work both independently and collaboratively within multidisciplinary teams to deliver technical solutions aligned to research and industrial objectives.
While my recent development work has primarily been in Python, MicroPython, and C, I am language agnostic and comfortable selecting and learning the most appropriate tools for a given problem or environment.
I develop systems primarily in Python, with additional experience in MicroPython and C, supporting data processing, system integration, and hardware interaction. I regularly build prototypes to test technical approaches and integrate APIs, sensors, and Linux-based systems. I am comfortable working across the full stack where required, selecting appropriate technologies based on project needs.
I have developed practical projects involving AI, sensing, and image-based analysis. This includes systems that process visual inputs, extract features, and generate structured outputs suitable for inspection-style tasks. I have worked with image processing techniques such as filtering, edge detection, and feature extraction, and understand how factors such as lighting, positioning, and image quality influence system performance.
I apply AI in practical, real-world environments, particularly where it intersects with sensing and decision-making systems. My focus is on how AI can be deployed effectively, progressing from cloud-based prototyping to local and edge-based deployment for performance, reliability, and data control. This reflects how AI is implemented in manufacturing environments.
I am comfortable working independently under guidance while managing my own workload, as well as contributing effectively within multidisciplinary teams. I have experience delivering multiple concurrent projects to deadlines, making day-to-day decisions on the use of complex technologies and selecting appropriate approaches based on constraints and requirements.
I communicate technical work clearly through written documentation, reporting, and stakeholder discussions. I have experience presenting technical concepts to both technical and non-technical audiences and working with stakeholders across engineering, IT, and operational teams, as well as industrial clients.
My approach is research-driven and iterative. I regularly evaluate multiple technical approaches, compare outcomes, and refine solutions based on performance and real-world constraints. I am comfortable exploring new and novel approaches where required to solve complex or unfamiliar engineering challenges.
I am highly motivated to apply for this role as I find the application of computer vision and AI within manufacturing genuinely compelling. It closely aligns with the direction I have been intentionally moving toward in my professional development, particularly in building practical systems that bridge sensing, data, and decision-making in real-world environments.
Recent Projects and Practical Experience
I have developed practical vision-based AI systems that process visual inputs and generate structured outputs suitable for inspection-style tasks.
A vision-language system that analyses images and produces structured, consistent outputs, demonstrating the use of AI for visual interpretation and decision support.
A vision-focused project exploring image analysis and AI-driven interpretation of visual data, with relevance to inspection, classification, and feature extraction tasks.
These projects demonstrate my ability to apply computer vision and AI techniques to real-world problems, including structured output generation and visual data analysis.
I have experience designing and implementing systems that capture and process physical-world data, aligning closely with industrial sensing and inspection workflows.
peak-mission-control.pages.dev ↗
A data aggregation and monitoring platform designed for industrial measurement systems, integrating hardware inputs with cloud-based processing and visualisation.
fed712f9.signalworks.pages.dev ↗
A sensing and data pipeline system supporting the capture, processing, and interpretation of real-world signals.
These systems demonstrate my ability to work across hardware and software layers, building end-to-end pipelines from data capture through to actionable insight.
In addition to vision systems, I have developed AI applications across other modalities, demonstrating flexibility in applying AI techniques to different problem domains.
A language processing tool designed to transform and adapt content across different contexts and audiences.
An AI-driven system for translating complex technical concepts into accessible language, demonstrating applied use of AI for communication and interpretation.
These projects highlight my broader capability in AI system design, integration, and practical deployment.
Professional Experience
Current Role
Technical project delivery within the AMRC, working across engineering, research, and IT teams. Integrating technology solutions within advanced manufacturing research settings.
Direct experience of the AMRC environment, quality management systems, and collaborative working culture, engaging with both industrial and academic partners.
Holds a higher level of security clearance for work within the AMRC environment than required for this role; immediately available for restricted projects without delay.
Designed end-to-end solutions for IoT and embedded measurement systems in industrial settings. Integrated hardware, software, and cloud layers for manufacturing data capture and analysis, delivering solutions to complex technical problems in high-value manufacturing contexts.
Progressed into a broader solutions role, leading internal IT and DevOps initiatives while supporting clients with system integration, platform adoption, and best-practice technical implementations.
Built cloud-based ultrasonic data aggregation platform for industrial measurement. Developed data pipelines for sensor data collection, processing, and analysis, working at the intersection of physical measurement systems and software.
9 yrs
Developed technical solutions to complex infrastructure challenges. Managed own time and resources across multiple concurrent projects.
Led a diverse technical team, managing workload and resources to project timescales. Drove continuous improvement of operational processes and team capabilities.
Excelled in written and verbal communication: technical reports, stakeholder presentations, process documentation.
Progressive responsibility across technical problem-solving, team leadership, and project delivery. Developed strong foundations in systematic troubleshooting and engineering rigour.
Technical problem-solving across diverse client environments.
Volunteering
School of Electrical and Electronic Engineering — supporting a multi-university collaboration with EEG data acquisition.
Technology strategy and delivery for a community charity, providing crucial technical backbone support on a pro bono basis.
School of Biosciences — supporting Dr Susannah Bird with field and lab work.
Peer Endorsements & Professional References
"I knew I could leave it and it would be sorted."
"He brought a level of clarity and structure to what could often be quite messy or fast-moving situations."
"I knew I could call on Connor to jump in and resolve problems."
Full endorsements available at connorbk.space/endorsements
Certifications & Professional Development
Core Skills
Education
2026
ISC2
CompTIA
2024 – 2025
The Sheffield College
2016 – 2018
Glasgow Clyde College
2012 – 2014
Vision West Nottinghamshire College
