Edge AI Engineer — PhD/Postdoctoral Development Programme

Disgrifiad o'r Cwmni

Edge AI & Intelligent Hardware Programme

Company Overview

Novomorphic is a new semiconductor design venture backed by Cadence Design Systems, Welsh Government, and CSA Catapult. We have been established to build critical semiconductor design capability in the UK.

Our focus is advanced integrated circuit and electronic system design, with particular strength in low-power intelligent hardware, edge AI, digital design, mixed-signal systems, and compound semiconductor technologies.

We are building Novomorphic from the ground up. That means every engineer who joins us will help shape the company, its technical capability, and its culture. We value technical excellence, ownership, curiosity, collaboration, and practical delivery.

The Opportunity

This is not a conventional graduate role. It is a structured industry development programme for PhD-level engineers and researchers who want to build deep expertise in Edge AI, intelligent hardware, and low-power AI deployment.

You will work on real engineering challenges involving machine learning models deployed on constrained hardware platforms, collaborating with semiconductor, FPGA, embedded systems, and software engineers across the full hardware/software stack.

The role is suited to candidates with strong research capability who want to apply AI knowledge in a commercial engineering environment where performance, efficiency, and practical deployment matter.

Role Overview

Novomorphic is seeking talented PhD graduates and postdoctoral researchers to join our growing Edge AI Engineering team.

You will contribute to the development, optimisation, compression, benchmarking, and deployment of AI models for low-power intelligent systems. Target areas include embedded AI, AI acceleration, edge inference, neuromorphic computing, CNNs, SNNs, and hardware-aware AI optimisation.

The role combines AI engineering, system-level thinking, embedded deployment, and exposure to advanced semiconductor and intelligent hardware technologies.

What You Will Do

AI Model Development and Optimisation

• Develop, train, optimise, and deploy machine learning models for edge and embedded AI applications.
• Work on model compression, quantisation, pruning, and optimisation for constrained hardware environments.
• Develop and evaluate CNN, SNN, and neuromorphic AI approaches for efficient low-power inference.
• Explore hardware-aware optimisation techniques for AI acceleration and embedded deployment.
• Benchmark, profile, and analyse AI system performance, efficiency, latency, and power consumption.
• Contribute to scalable Edge AI workflows, reusable methodologies, and internal engineering IP.

Embedded and Hardware-Aware AI Engineering

• Deploy AI workloads onto embedded and constrained hardware platforms.
• Collaborate with FPGA, semiconductor, firmware, embedded, and systems engineers to optimise AI performance across hardware/software boundaries.
• Support integration of AI inference pipelines into intelligent hardware platforms.
• Contribute to system-level optimisation for low-power and energy-constrained AI systems.
• Translate research concepts into practical engineering outputs suitable for deployment.

Collaboration and Technical Growth

• Work closely with AI researchers, IC designers, embedded engineers, FPGA engineers, and technical mentors.
• Participate in technical reviews, architecture discussions, design investigations, and engineering problem-solving activities.
• Build capability across Edge AI workflows, hardware-aware optimisation, embedded deployment, and intelligent hardware integration.
• Progress towards independent technical ownership within 6–12 months.

What You Will Develop

Through the programme, you will build practical capability in:

• Edge AI system development
• Machine learning model training and optimisation
• CNN, SNN, and neuromorphic architectures
• AI model compression and quantisation
• Hardware-aware AI optimisation
• Deployment of AI models on constrained hardware platforms
• AI acceleration architectures and embedded inference workflows
• Low-power and energy-constrained AI system design
• Hardware/software co-design methodologies
• AI benchmarking, profiling, and performance analysis
• FPGA and embedded AI integration
• Cross-disciplinary semiconductor and AI engineering collaboration

What We Are Looking For

We are looking for technically strong, research-driven candidates with a clear interest in Edge AI, embedded intelligence, low-power AI systems, and intelligent hardware technologies.

Essential Requirements

• PhD or postdoctoral experience in one or more of the following areas:
  • Artificial Intelligence
  • Machine Learning
  • Electronic Engineering
  • Computer Engineering
  • Computer Science with strong systems or hardware relevance
  • Embedded Systems
  • Neuromorphic Computing
  • A closely related field
• Strong understanding of machine learning fundamentals.
• Evidence of hands-on AI model development, optimisation, deployment, or hardware-aware AI research.
• Interest in Edge AI and constrained hardware deployment.
• Strong analytical and problem-solving skills.
• Ability to work across hardware and software domains.
• Clear communication and willingness to document technical work properly.

Desirable Experience

Experience through research, publications, prototypes, coursework, open-source work, or practical development in areas such as:

• Edge AI or embedded AI systems
• CNNs, SNNs, or neuromorphic AI
• AI model optimisation, quantisation, pruning, or compression
• AI accelerators or hardware-aware AI workflows
• FPGA or embedded AI deployment
• Python and machine learning frameworks
• Embedded Linux environments
• Hardware/software co-design
• Low-power intelligent systems
• AI benchmarking and performance analysis
• Heterogeneous compute or accelerator-based systems
• Embedded inference and deployment pipelines

Familiarity with any of the following tools or environments is useful but not essential:

• PyTorch
• TensorFlow
• ONNX
• CUDA or AI acceleration toolchains
• Python scripting and automation
• FPGA development environments
• MATLAB / Simulink
• Cadence or hardware design environments
• Embedded Linux environments
• Git and software version control

Previous industry experience is not required, but strong hands-on AI engineering or deployment experience is important.

We Value Engineers Who

• Take ownership and follow through.
• Enjoy solving difficult engineering and AI problems.
• Are curious, practical, and willing to learn quickly.
• Can work independently without disappearing into a silo.
• Collaborate well across hardware and software disciplines.
• Communicate clearly, especially when raising risks or blockers.
• Are comfortable in a start-up environment where priorities can move quickly.
• Want to build real low-power AI and intelligent hardware capability, not just research prototypes.

What Success Looks Like

Early success in this role means:

• Strong engagement with onboarding and technical development.
• Good progress in Edge AI workflows and hardware-aware optimisation.
• High-quality delivery on assigned engineering, optimisation, research, or deployment tasks.
• Active participation in technical reviews and multidisciplinary engineering discussions.
• Growing confidence in deploying and optimising AI models on constrained hardware.
• Meaningful contribution to internal IP, innovation activity, and customer projects.
• Clear progression towards independent technical ownership within 6–12 months.

Why Join Novomorphic?

At Novomorphic, you will:

• Work on next-generation Edge AI and intelligent hardware technologies.
• Collaborate with experienced semiconductor, embedded, FPGA, and AI engineers.
• Build highly sought-after expertise in low-power AI systems and intelligent hardware deployment.
• Contribute to real customer projects, internal platforms, and reusable engineering IP.
• Gain exposure to advanced semiconductor, embedded, mixed-signal, and intelligent hardware technologies.
• Help strengthen the UK semiconductor and Edge AI ecosystem.
• Build a long-term career at the intersection of AI and hardware innovation.

Benefits

Novomorphic’s benefits package includes:

• 28 days’ annual leave plus bank holidays
• Salary sacrifice pension scheme
• Annual discretionary bonus scheme
• Life assurance
• Private medical insurance
• Additional benefits tailored to employee needs

Location and Working Model

This role is based in Cardiff, Wales. Working arrangements may vary depending on project and business requirements.

Candidates must have the right to work in the UK or be eligible for sponsorship, where applicable.