
Your Tech Future
Data Tooling Engineer Computer Vision
Job Description
Salary: £35,000 - 75,000 per year
Requirements:- Commercial experience developing tools, applications or workflow automation using Python.
- Experience designing technical solutions that improve operational or production workflows.
- Experience working with APIs, systems integrations or data-transfer processes.
- Confidence handling structured data, files and metadata.
- An understanding of software-engineering fundamentals, including maintainable code, testing, debugging and version control.
- Experience gathering requirements and building practical tools for end users.
- Strong problem-solving skills and the ability to investigate complex technical or data-related issues.
- The ability to communicate effectively with both technical and non-technical colleagues.
- Strong attention to detail, particularly around data accuracy and reliability.
- Experience working with image, video or other visual datasets.
- Experience developing user interfaces, particularly using PyQt or similar technologies.
- Familiarity with data annotation platforms or annotation workflows.
- Understanding of image classification, object detection or segmentation.
- Experience with data pipelines, dataset versioning or MLOps practices.
- Familiarity with SQL or database technologies.
- Experience working with cloud-based data or storage platforms.
- Knowledge of PyTorch datasets or computer vision model-training workflows.
- Understanding of active learning or human-in-the-loop systems.
- Experience using Git and collaborative development workflows.
- Experience within robotics, autonomous systems, VFX, animation, gaming or another image-intensive technical environment.
- Design, develop and maintain our internal tools supporting the creation and management of computer vision datasets.
- Build Python-based applications, scripts and automation to improve annotation and data-processing workflows.
- Develop intuitive tools and interfaces for technical and non-technical users.
- Integrate annotation platforms and internal systems using APIs and other appropriate technologies.
- Automate repetitive data preparation, validation and quality-assurance processes.
- Work with large-scale image, video and associated metadata.
- Identify workflow bottlenecks and develop technical solutions to improve efficiency and reliability.
- Implement validation and quality-control processes to identify incomplete, inconsistent or incorrectly structured data.
- Support dataset organisation, versioning, transformation and export.
- Troubleshoot tooling, integration and data-processing issues.
- Work closely with Machine Learning and Computer Vision Engineers to understand dataset and model requirements.
- Gather feedback from users and continually improve tooling and workflows.
- Produce clear technical documentation and user guidance.
- Contribute to appropriate testing, code review and deployment practices.
- AI
- Cloud
- Computer Vision
- Git
- Support
- Machine Learning
- MLOps
- PyTorch
- Python
- Robotics
- SQL
More:
We are hiring a Data Tooling Engineer for a remote role in the UK, with salary dependent on experience. We build internal tools and workflows that support advanced computer vision and AI systems, helping to create, manage and quality-check the datasets underpinning our machine learning pipeline. This is a hands-on tooling and engineering role focused on Python development, workflow automation, systems integration and user-focused problem solving. You will work closely with Machine Learning and Computer Vision Engineers to improve annotation efficiency, data quality and the reliability of our autonomous systems, with the opportunity to influence how sophisticated computer vision systems are developed.
last updated 34 week of 2026
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About Your Tech Future

Your Tech Future
UK
IT
Skills & Technologies
Inferred from job description
Salary Insight
£55,000
This role
£60,000
UK median
This salary is 8% below the UK median for Software Engineers (£60,000/yr).
Based on 2024–2025 UK technology sector benchmarks