Machine Learning Engineer
Location: London (Hybrid, approx. 3 days per week onsite)
Salary: Up to £65,000 (depending on experience)
NOTE: Candidates must be eligible for UK Developed Vetting (DV)
This is an opportunity to work at the forefront of applied AI within highly secure and mission-critical environments. You’ll be contributing to the development of advanced machine learning and generative AI solutions that deliver real-world impact across complex, high-stakes domains.
You will be embedded within a multidisciplinary engineering team, working across the end-to-end delivery of machine learning systems. This includes building models, running experiments, and deploying scalable solutions using modern cloud and MLOps tooling.
Key Responsibilities Include:
* Designing and developing machine learning models (e.g. classification, forecasting, anomaly detection)
* Supporting experimentation cycles: hypothesis definition, testing, and evaluation
* Contributing to the deployment of models into production environments
* Building and maintaining ML pipelines using AWS services
* Assisting in the development of GenAI/LLM-based applications (e.g. prompt engineering, RAG pipelines)
* Implementing best practices in experiment tracking, model versioning, and reproducibility
* Monitoring model performance and supporting continuous improvement
* Collaborating with engineers, data scientists, and stakeholders across the delivery lifecycle
Required Skills & Experience
* Minimum 1+ year of commercial experience in machine learning or data science
* Strong Python skills with experience in ML frameworks such as scikit-learn, PyTorch, TensorFlow, or XGBoost
* Exposure to AWS services (e.g. S3, Lambda, SageMaker)
* Understanding of core ML concepts: model evaluation, validation, and experimentation
* Familiarity with MLOps or experiment tracking tools (e.g. MLflow, Weights & Biases)
* Awareness of LLMs or generative AI concepts
* Strong problem-solving ability and willingness to learn in a fast-paced environment
* Ability to communicate technical concepts clearly
Desirable Experience
* Experience with LLM frameworks (e.g. LangChain)
* Knowledge of vector databases or RAG architectures
* Exposure to Docker or containerised environments
* Familiarity with data processing tools (e.g. Spark, Dask)
* Understanding of CI/CD or infrastructure as code
If you are an ambitious Machine Learning Engineer looking to build real-world AI systems in a high-impact environment, apply today.