Research Software Engineer in Edge Devices & Machine Learning Deployment

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

Essential

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.

Desirable:

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. 

Requisition ID: 28336