Embedded Machine Vision Engineer – Hybrid (Aberdeen)

Salary: £70,000 – £80,000
Location: Aberdeen – Hybrid – 3 days from home a week

 

 

Zed Rail’s client, an Aberdeen-based technology company, is leading the way in embedded vision systems for real-time threat and risk detection. Their work combines advanced near-infrared (IR) camera sensors with deterministic AI models to identify anomalies, hazards, and safety risks.

 

This is a rare opportunity to join a company developing cutting-edge embedded vision and AI technology, with the balance of in-office collaboration and home working. You’ll spend two days per week at their Aberdeen site, working closely with the engineering team, and three days per week working remotely.

 

The ideal candidate will be a strong embedded software engineer who has recently moved into AI and machine learning for vision systems, and is eager to continue working in that space. You’ll be working on certifiable, fixed AI models (no runtime learning), helping to deliver reliable, reproducible results in safety-critical systems.

 

 

Key responsibilities:

Develop and optimize real-time embedded vision algorithms in C/C++
Work with near-IR camera sensors to classify visual and behavioral characteristics
Integrate fixed AI/ML models (e.g. CNNs) into embedded systems
Ensure deterministic, certifiable software execution under memory and timing constraints
Evaluate model performance under varied environmental conditions (lighting, motion, etc.)
Collaborate closely with software, hardware, and certification engineers

 

 

Required Skills & Experience:

Strong embedded software development experience (C/C++, Linux, real-time systems)
Proven background in embedded machine vision or image pipelines
Hands-on with IR, CMOS, or similar camera/imaging systems
Practical understanding of embedded AI/ML techniques (e.g. CNNs, segmentation, shape tracking)
Comfortable working in memory- and timing-constrained environments

 

 

Preferred Qualifications:

Degree or MSc in Computer Vision, Embedded Systems, or related field
Experience developing software for safety-critical systems
Familiarity with IEC 61508 or similar certification standards

 

 

This is a fantastic opportunity for an engineer passionate about embedded AI and real-time vision to work on impactful technology that directly contributes to driver and passenger safety. You’ll be joining a small, expert team at the forefront of embedded machine vision, with the flexibility of hybrid working

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