Senior Edge AI Engineer

Company Overview

Novomorphic is a UK semiconductor and systems design company focused on system-first secure Edge AI.

We design and deliver advanced electronics where power, thermal performance, RF behaviour, latency, reliability, and security constraints matter. Our work spans edge AI systems, digital IC design, analogue and mixed-signal systems, FPGA platforms, embedded systems, and compound semiconductor technologies.

We work through focused delivery, paid pilots, demonstrators, partner-enabled projects, and CR&D programmes. Our aim is to turn complex technical work into practical engineering outcomes, strong partner confidence, and clear commercial proof-points.

We are building Novomorphic from the ground up. We value technical excellence, ownership, curiosity, collaboration, and practical delivery/

The Opportunity

This is a senior engineering role for an experienced AI, machine learning or embedded intelligence engineer who wants to build practical AI systems for real hardware.

You will work across edge AI, anomaly detection, adaptive control, model optimisation, data pipelines and deployment onto constrained embedded or FPGA-enabled platforms.

The role is suited to candidates who can combine strong machine learning judgement with practical engineering delivery. We are not looking for pure research in isolation. We are looking for someone who can help turn models, algorithms and data into working systems.

Role Overview

Novomorphic is seeking a Senior Edge AI Engineer to help lead the design, development, optimisation and deployment of AI and machine learning capability for low-power intelligent hardware and electronic systems.

You will contribute to AI systems for edge devices, smart electronics, industrial automation, anomaly detection, motor-control intelligence, sensor data analysis and future semiconductor applications.

The role combines hands-on machine learning development, embedded deployment, model optimisation, hardware-aware engineering, technical leadership and collaboration with FPGA, embedded firmware, digital hardware and system architecture teams.

What You Will Do

Edge AI and Machine Learning

• Design, train, evaluate and improve machine learning models for edge and embedded use cases.
• Develop models for anomaly detection, adaptive control, sensor intelligence, industrial data, video data, time-series data and cyber-physical systems.
• Optimise models for low-power, low-latency and resource-constrained deployment.
• Work on model compression, quantisation, pruning, knowledge distillation and hardware-aware optimisation.
• Build clear benchmarking workflows using relevant accuracy, latency, power, robustness and reliability measures.
• Support the deployment of AI models onto embedded processors, FPGA-enabled platforms and edge hardware.
• Produce clear technical documentation, model notes, evaluation reports and review material.

Data, Tooling and Deployment

• Build and maintain datasets, synthetic data pipelines, lab data capture workflows and validation datasets.
• Create reproducible training and evaluation workflows using Python and modern machine learning frameworks.
• Work with embedded firmware and FPGA engineers to define practical deployment paths for trained models.
• Develop test scripts, prototype demos and analysis tools to support customer, grant-funded and internal projects.
• Support integration of AI models with sensors, FPGA data paths, firmware interfaces and system-level demonstrators.

Technical Leadership and Collaboration

• Provide senior technical guidance to junior AI, data and embedded ML engineers.
• Work closely with FPGA engineers, embedded software engineers, IC designers, hardware engineers and system architects.
• Participate in design reviews, technical discussions, debug sessions and project planning.
• Identify technical risks early and help define practical mitigation plans.
• Support proposals, customer discussions and innovation projects where edge AI is a key capability.
• Help build reusable AI and embedded intelligence capability inside Novomorphic.

What You Will Develop

Through the role, you will build and strengthen practical capability in:

• Advanced edge AI and embedded machine learning engineering
• Anomaly detection, adaptive control and intelligent sensing methods
• Hardware-aware AI model optimisation
• Model compression, quantisation and deployment workflows
• AI integration with FPGA, embedded firmware and intelligent hardware systems
• Synthetic data, data engineering and benchmarking methodologies
• Python-based machine learning, analysis and automation workflows
• Low-power and latency-aware AI system design
• Reusable AI IP, model evaluation and technical reporting
• Cross-disciplinary semiconductor, FPGA, embedded and AI collaboration

What We Are Looking For

We are looking for a technically strong, practical and commercially aware AI engineer who can build models that work in real engineering systems. You should be comfortable moving between research ideas, data, software, embedded constraints, hardware interfaces and delivery milestones.

Essential Requirements

• Strong industry or applied research experience in machine learning, deep learning, edge AI or embedded intelligence.
• Strong Python skills and practical experience with frameworks such as PyTorch, TensorFlow, JAX or similar.
• Experience building, training, evaluating and improving machine learning models.
• Good understanding of model performance, robustness, overfitting, dataset quality and benchmarking.
• Experience or strong interest in deploying models on constrained hardware, embedded platforms or edge systems.
• Ability to work across multidisciplinary engineering domains.
• Clear communication and willingness to document technical work properly.
• Ability to mentor junior engineers and take ownership of technical delivery.

Desirable Experience

Experience through industry work, research, prototypes, coursework, lab work or practical development in areas such as:

• Edge AI or embedded ML deployment
• Anomaly detection or cyber-physical system monitoring
• Computer vision, graph neural networks or time-series modelling
• Adaptive control, motor-twin methods or digital-twin methods
• Model compression, quantisation, pruning or hardware-aware neural architecture design
• ONNX, TensorRT, Vitis AI, TVM or similar deployment tooling
• C/C++ awareness for embedded integration
• FPGA or digital hardware awareness
• Synthetic data generation and validation
• MLOps, experiment tracking or reproducible model workflows
• Experience with sensor data, industrial systems, energy systems, robotics or defence-related applications

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

• PyTorch, TensorFlow, JAX or similar
• Python data science and analysis workflows
• ONNX, TensorRT, Vitis AI, TVM or similar
• MATLAB / Simulink
• Git and version control workflows
• Linux development environments
• Embedded software or FPGA development environments
• Data visualisation, benchmarking and experiment tracking tools

Previous start-up experience is not required, but strong hands-on engineering experience and practical delivery judgement are important.

We Value Engineers Who

• Take ownership and follow through.
• Enjoy solving difficult engineering problems.
• Are curious, practical, and willing to learn quickly.
• Can work independently without disappearing into a silo.
• Collaborate well with engineers from different 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 engineering capability, not just write documents or papers.

What Success Looks Like

Early success in this role means

• Strong engagement with onboarding, project delivery and technical leadership.
• Good progress in building reusable edge AI workflows and model evaluation methods.
• High-quality delivery on assigned model development, optimisation, deployment, research or documentation tasks.
• Active participation in multidisciplinary design reviews and engineering discussions.
• Growing ownership of edge AI architecture, model quality and deployment decisions.
• Meaningful contribution to customer projects, internal platforms, funded innovation programmes and reusable IP.

Why Join Novomorphic?

At Novomorphic, you will

• Work on next-generation semiconductor, edge AI, FPGA and intelligent hardware technologies.
• Use industry-standard engineering tools and workflows across semiconductor, FPGA, embedded and system design.
• Learn directly from experienced semiconductor, FPGA, embedded, AI and systems engineers.
• Contribute to real customer projects, internal platforms, reusable engineering IP and funded innovation programmes.
• Gain exposure to advanced low-power, intelligent, digital, mixed-signal and compound semiconductor technologies.
• Help strengthen the UK semiconductor and intelligent hardware ecosystem.
• Build a long-term career in advanced semiconductor and electronic systems engineering.

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.