13543- Applications Developer
| Dyddiad hysbysebu: | 17 Rhagfyr 2025 |
|---|---|
| Cyflog: | £34,610 i £42,254 bob blwyddyn |
| Oriau: | Llawn Amser |
| Dyddiad cau: | 14 Ionawr 2026 |
| Lleoliad: | Edinburgh, Scotland |
| Gweithio o bell: | Hybrid - gweithio o bell hyd at 3 ddiwrnod yr wythnos |
| Cwmni: | University of Edinburgh |
| Math o swydd: | Dros dro |
| Cyfeirnod swydd: | 13543 |
Crynodeb
Grade UE06: £34,610 - £42,254 per annum
EPCC, College of Science and Engineering
Full-time: 35 hours
Fixed term: 3 years with possibility of extension
Up to 4 posts available
The Opportunity:
Join EPCC, the UK’s National Supercomputing Centre, in a highly technological and fast-moving field. We are seeking up to four motivated Application Developers. This role is for you if you like understanding what problems other organisations are trying to solve with AI. You like to design solutions, develop machine learning/AI pipelines and deploy these pipelines in production. You can demonstrate experience in programming languages (e.g., Python, R, C++), software engineering (e.g., coding skills, testing frameworks, version control, documentation), use of distributed infrastructure (e.g., scaling, containers), data engineering (e.g., databases, streaming, MLops), and machine learning (e.g., PyTorch, TensorFlow, LLM models). You are motivated to learn and apply new technologies, tools and methods. For the Application Consultant role, that you have experience interacting with external problem stakeholders to design, implement and deploy solutions.
This post is full-time (35 hours per week). We are also open to considering requests for hybrid working (on a non-contractual basis) that combines a mix of remote and regular on-campus working.
Your skills and attributes for success:
You like to understand what problems other organisations are trying to solve with AI and like to design solutions, develop machine learning/AI pipelines and deploy these pipelines in production.
You can demonstrate experience in programming languages (e.g., Python, R, C++), software engineering (e.g., coding skills, testing frameworks, version control, documentation).
You have experience using distributed infrastructure (e.g., scaling, containers), data engineering (e.g., databases, streaming, MLops), and machine learning (e.g., PyTorch, TensorFlow, LLM models).
You are motivated to learn and apply new technologies, tools and methods.
EPCC, College of Science and Engineering
Full-time: 35 hours
Fixed term: 3 years with possibility of extension
Up to 4 posts available
The Opportunity:
Join EPCC, the UK’s National Supercomputing Centre, in a highly technological and fast-moving field. We are seeking up to four motivated Application Developers. This role is for you if you like understanding what problems other organisations are trying to solve with AI. You like to design solutions, develop machine learning/AI pipelines and deploy these pipelines in production. You can demonstrate experience in programming languages (e.g., Python, R, C++), software engineering (e.g., coding skills, testing frameworks, version control, documentation), use of distributed infrastructure (e.g., scaling, containers), data engineering (e.g., databases, streaming, MLops), and machine learning (e.g., PyTorch, TensorFlow, LLM models). You are motivated to learn and apply new technologies, tools and methods. For the Application Consultant role, that you have experience interacting with external problem stakeholders to design, implement and deploy solutions.
This post is full-time (35 hours per week). We are also open to considering requests for hybrid working (on a non-contractual basis) that combines a mix of remote and regular on-campus working.
Your skills and attributes for success:
You like to understand what problems other organisations are trying to solve with AI and like to design solutions, develop machine learning/AI pipelines and deploy these pipelines in production.
You can demonstrate experience in programming languages (e.g., Python, R, C++), software engineering (e.g., coding skills, testing frameworks, version control, documentation).
You have experience using distributed infrastructure (e.g., scaling, containers), data engineering (e.g., databases, streaming, MLops), and machine learning (e.g., PyTorch, TensorFlow, LLM models).
You are motivated to learn and apply new technologies, tools and methods.