Machine Learning Engineer

Experis (Austria); Newcastle upon Tyne; On-site; GBP 60,000 - 95,000; Full time

Job summary

Unknown is seeking a Machine Learning Engineer to work on defence and national security projects in Newcastle upon Tyne. You will develop, train and evaluate ML/DL models, optimise performance for constrained environments and drive production-ready deployments across client sites in the UK.

The role involves handling complex datasets, applying feature engineering, and contributing to applied research while collaborating with cross-functional teams in a fast-paced setting.

Qualifications

• Strong Python programming skills and solid software engineering practices.
• Hands-on experience training and tuning deep learning models using PyTorch, TensorFlow or similar frameworks.
• Strong understanding of machine learning algorithms, mathematics, statistics and model evaluation.
• Experience with model deployment, productionisation and retraining.
• Expertise in at least one area such as computer vision, audio, time series forecasting, reinforcement learning or few-shot learning.
• Exposure to edge computing, embedded AI, model optimisation, explain ability or AI security would be beneficial.
• Strong communication skills and the ability to work collaboratively in a fast-paced technical environment.
• Experience in defence or national security is advantageous, but not essential.

Responsibilities

• Develop, train and evaluate machine learning and deep learning models
• Optimise model performance, inference and deployment in constrained environments
• Take models from experimentation and proof of concept through to production
• Work with complex datasets, feature engineering and model validation
• Contribute to applied research and the development of future defence-relevant capabilities
• Collaborate with technical teams and share knowledge across the business

Skills

Python

Deep learning

Model deployment

Edge computing

Explainable AI

AI security

Collaboration

Communication

Tools

PyTorch

TensorFlow

Job description

Machine Learning Engineer – Defence & National Security

Location: Newcastle upon Tyne

Security Clearance: Must be eligible for UK SC clearance

I’m working with a growing technical consultancy looking for Machine Learning Engineers to work on challenging AI and machine learning projects across defence, national security and other complex sectors.

This is a hands on engineering role for someone who wants to work beyond off the shelf models, developing, training, evaluating and optimising machine learning solutions for real world applications.

The role:

• Develop, train and evaluate machine learning and deep learning models
• Optimise model performance, inference and deployment in constrained environments
• Take models from experimentation and proof of concept through to production
• Work with complex datasets, feature engineering and model validation
• Contribute to applied research and the development of future defence-relevant capabilities
• Collaborate with technical teams and share knowledge across the business

What we're looking for:

• Strong Python programming skills and solid software engineering practices
• Hands-on experience training and tuning deep learning models using PyTorch, TensorFlow or similar frameworks
• Strong understanding of machine learning algorithms, mathematics, statistics and model evaluation
• Experience with model deployment, productionisation and retraining
• Expertise in at least one area such as computer vision, audio, time series forecasting, reinforcement learning or few-shot learning
• Exposure to edge computing, embedded AI, model optimisation, explain ability or AI security would be beneficial
• Strong communication skills and the ability to work collaboratively in a fast-paced technical environment

Experience in defence or national security is advantageous, but not essential.

Location and travel: Newcastle-based, with regular travel to client sites across the UK. Assignments may involve two to three days per week on-site, or occasional periods of full-time site-based work. Travel expenses and accommodation are covered.