Applied AI Engineer – Deep-Tech Manufacturing

Darogan Limited; Bridgend, Neath; On-site; GBP 15,000 - 19,000; Full time

Benefits offered by this job

25 hours/week

6-month contract

NLW salary

Tech Talent Cymru programme

Mentoring

Job summary

TrimTabs Ltd is building its in-house AI capability and seeks a technically strong graduate to lead applied AI on the shop floor and microscopy image analysis. You will influence material characterisation and process decisions while working closely with science and manufacturing teams.

The role combines 1) applied AI and data analysis, 2) AI systems and infrastructure, and 3) capability building across the business.

Qualifications

• Degree in AI, computer science, physics, engineering, mathematics or related STEM discipline; MSc in AI or ML welcome
• Strong programming ability, ideally Python, with ML and data libraries
• Working knowledge of ML fundamentals and judgement to choose simple vs. complex methods
• Clear communication to non-AI colleagues
• Self-starting and practical in a small company where AI is being built from scratch
• Eligible to work in the UK and able to work from Bridgend site
• Exposure to computer vision or image analysis, especially microscopy imagery
• Experience deploying/maintaining models in production/lab environments
• Interest in materials science or advanced manufacturing
• Experience delivering training or mentoring to non-technical colleagues

Responsibilities

• Develop and apply AI and computer vision methods to extract information from microscopy images
• Support data analysis across characterisation and production datasets to identify patterns
• Apply AI techniques to engineering and related processes under development

Skills

Python

ML

Data analysis

Computer vision

MLOps

Communication

Education

AI/CS/Engineering degree

Tools

Python

PyTorch

TensorFlow

Job description

TrimTabs Ltd is building its in-house AI capability and seeks a technically strong graduate to lead applied AI on the shop floor and microscopy image analysis. You will influence material characterisation and process decisions while working closely with science and manufacturing teams.

The role combines 1) applied AI and data analysis, 2) AI systems and infrastructure, and 3) capability building across the business.