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- Tasks: Design and implement software for deploying ML models on edge devices.
- Company: Join Newcastle University, a global leader in research and innovation.
- Benefits: Enjoy a collaborative environment with opportunities for cross-industry engagement.
- Why this job: Make a real-world impact in healthcare, transport, and energy security through cutting-edge AI.
- Qualifications: Bachelor's or Master's in Computer Science or related field; experience with edge platforms required.
- Other info: Newcastle University values diversity and offers a welcoming environment for all.
The predicted salary is between 28800 - 48000 £ per year.
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Research Software Engineer in Edge Devices & Machine Learning Deployment, Newcastle upon Tyne
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Client:
Newcastle University
Location:
Newcastle upon Tyne, United Kingdom
Job Category:
Other
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EU work permit required:
Yes
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Job Reference:
846fd3f58720
Job Views:
5
Posted:
18.07.2025
Expiry Date:
01.09.2025
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Job Description:
The Role
Newcastle University invites applications for a Research Software Engineer to join the EPSRC-funded National EdgeAI Hub for Real Data. This role will contribute to Work Stream 5, focusing on the validation of data-sensitive applications in edge AI, addressing challenges in cybersecurity, data quality, and real-time AI performance.
This research hub, tackles the intricate challenges of cyber-disturbances and data quality in Edge Computing (EC) environments supporting AI algorithms. The role involves close collaboration with a diverse and multidisciplinary team across the UK to validate the edge AI innovations in critical sectors such as healthcare, transport, and energy security. The role will naturally integrate with other research streams within the consortium, providing opportunities for cross-stream collaboration and engagement with both academic and industrial partners.
Join a world-class research environment at Newcastle University and contribute to cutting-edge advancements in Edge AI and cybersecurity for real-world impact. As part of the National EdgeAI Hub, you will have the opportunity to work alongside leading academics, collaborate with industry partners, and apply your expertise to groundbreaking use cases in healthcare, transport, energy, and beyond.
For more information about the hub’s mission and objectives, visit .
How to Apply
To apply, please submit an online application including your CV and a cover letter outlining how you meet the essential criteria for this role.
Informal enquiries may be addressed to: Professor Phil James: Dr Ellis Solaiman: Professor Raj Ranjan:
Key Accountabilities
- Design and implement software pipelines to deploy ML models on edge devices with real-time inference capabilities.
- Optimize machine learning models (e.g., quantization, pruning) for edge hardware to balance accuracy, latency, and power consumption.
- Integrate edge AI solutions with sensor data streams and device hardware.
- Develop observability tools for monitoring model quality, drift, and system health on deployed devices.
- Write clean, efficient, and well-documented code with comprehensive testing.
- Stay updated on the latest advancements in edge AI frameworks, hardware accelerators, and deployment strategies.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field.
- Experience deploying machine learning models on edge platforms (e.g., NVIDIA Jetson, Raspberry Pi, ARM Cortex).
- Proficiency in programming languages such as Python, C/C++, or Rust.
- Familiarity with ML frameworks and tools like TensorFlow Lite, PyTorch Mobile, ONNX Runtime, and Edge Impulse.
- Experience with model optimization techniques (quantization, pruning, distillation).
- Understanding of communication protocols (MQTT, CoAP, HTTP) for edge environments.
- Excellent communication and documentation skills.
- Familiarity with edge AI accelerators (e.g., Hailo, ARM Ethos, NVidia).
- Knowledge of monitoring frameworks for model observability and quality metrics.
- Prior experience with containerization (Docker).
Newcastle University is a global University where everyone is treated with dignity and respect. As a University of Sanctuary, we aim to provide a welcoming place of safety for all, offering opportunities to people fleeing violence and persecution.
We are committed to being a fully inclusive university which actively recruits, supports and retains colleagues from all sectors of society. We value diversity as well as celebrate, support and thrive on the contributions of all of our employees and the communities they represent. We are proud to be an equal opportunities employer and encourage applications from individuals who can complement our existing teams, we believe that success is built on having teams whose backgrounds and experiences reflect the diversity of our university and student population.
At Newcastle University we hold a silver award in recognition of our good employment practices for the advancement of gender equality. We also hold a Bronze award in recognition of our work towards tackling race inequality in higher education REC. We are a employer and will offer an interview to disabled applicants who meet the essential criteria for the role as part of the offer and interview scheme.
In addition, we are a member of the Euraxess initiative supporting researchers in Europe.
Please note that if you are NOT a passport holder of the country for the vacancy you might need a work permit. Check our Blog for more information.
Bank or payment details should not be provided when applying for a job. Eurojobs.com is not responsible for any external website content. All applications should be made via the \’Apply now\’ button.
Created on 18/07/2025 by TN United Kingdom
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Research Software Engineer in Edge Devices & Machine Learning Deployment employer: Newcastle University
Contact Detail:
Newcastle University Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Software Engineer in Edge Devices & Machine Learning Deployment
✨Tip Number 1
Familiarise yourself with the latest advancements in edge AI frameworks and hardware accelerators. This knowledge will not only help you during interviews but also demonstrate your genuine interest in the field.
✨Tip Number 2
Engage with the research community by attending relevant conferences or webinars. Networking with professionals in the field can provide insights into the role and may even lead to valuable connections at Newcastle University.
✨Tip Number 3
Prepare to discuss specific projects where you've deployed machine learning models on edge devices. Be ready to explain the challenges you faced and how you optimised models for performance, as this will showcase your practical experience.
✨Tip Number 4
Brush up on your communication skills, especially when it comes to explaining complex technical concepts. Being able to articulate your ideas clearly will be crucial when collaborating with multidisciplinary teams.
We think you need these skills to ace Research Software Engineer in Edge Devices & Machine Learning Deployment
Some tips for your application 🫡
Tailor Your Cover Letter: Make sure to customise your cover letter to highlight how your skills and experiences align with the specific requirements of the Research Software Engineer role. Mention your experience with edge devices and machine learning deployment, as well as any relevant projects you've worked on.
Showcase Relevant Experience: In your CV, emphasise your experience deploying machine learning models on edge platforms like NVIDIA Jetson or Raspberry Pi. Include specific examples of projects where you optimised models for performance and efficiency.
Highlight Technical Skills: Clearly list your programming skills in languages such as Python, C/C++, or Rust, and mention your familiarity with ML frameworks like TensorFlow Lite and PyTorch Mobile. This will demonstrate your technical proficiency to the hiring team.
Proofread Your Application: Before submitting, carefully proofread your CV and cover letter for any spelling or grammatical errors. A polished application reflects your attention to detail and professionalism, which are crucial in a research environment.
How to prepare for a job interview at Newcastle University
✨Showcase Your Technical Skills
Be prepared to discuss your experience with deploying machine learning models on edge devices. Highlight specific projects where you've optimised models for performance and power consumption, and be ready to explain the techniques you used, such as quantization or pruning.
✨Understand the Role's Context
Familiarise yourself with the National EdgeAI Hub's mission and objectives. Understanding how your role fits into the larger picture of cybersecurity and data quality in edge AI will demonstrate your genuine interest and commitment to the position.
✨Prepare for Collaborative Questions
Since the role involves working with a multidisciplinary team, expect questions about teamwork and collaboration. Think of examples from your past experiences where you successfully worked with others to achieve a common goal, especially in a research or technical setting.
✨Ask Insightful Questions
Prepare thoughtful questions to ask at the end of the interview. Inquire about the current challenges the team is facing in edge AI or how they measure success in their projects. This shows your enthusiasm and helps you gauge if the role aligns with your career goals.
