Machine Learning Engineer - SC Cleared

You will design, train and optimise high-performance machine learning models and integrate them into production environments., * Developing custom neural network architectures using PyTorch

• Building and curating high-quality training datasets
• Performing data augmentation, feature extraction and labelling
• Running structured training, validation and optimisation cycles
• Converting models for efficient inference using tools such as ONNX or similar
• Working with quantised models for performance-constrained environments
• Collaborating closely with software engineers on integration
• Communicating technical work clearly to both technical and non-technical stakeholders
• You may also contribute to broader Python-based software development activities.

Do you have experience in Software deployment?, · Degree in Computer Science, Engineering, Mathematics or related discipline

· Strong Python development capability

· Strong C or C++ skills

· Deep understanding of neural network architectures such as RNNs and Transformers

· Experience building and training models using pure PyTorch

· Experience designing and managing training pipelines

· Experience with model optimisation and conversion for deployment

· Strong understanding of dataset preparation and feature engineering

· Excellent communication and technical writing ability

The Opportunity:

You will join a technically capable team working on complex engineering challenges where quality, rigour and performance are critical.

This is an on-site role due to the nature of the work.

If you are confident building models from scratch and want to work on technically demanding projects, we would welcome a confidential conversation.

NexGen Associates are partnered with a highly technical engineering organisation in the South West who are expanding their advanced AI capability. This is a hands-on engineering role for someone who builds and trains neural networks from first principles. It is not a deployment-only or notebook-based data science position. You will work on real-world machine learning challenges where model performance, data quality and deployment efficiency genuinely matter.