Salary: £40,000 - 60,000 per year Requirements: BSc or MSc in Computer Science, Mathematics, Statistics, Physics, Quantum, or a closely related discipline 2 years of industry experience developing and deploying machine learning models Strong programming skills in Python for machine learning and scientific computing Experience developing, training, and optimising machine learning models Familiarity with common ML tools and frameworks such as PyTorch, pandas, and scikit-learn Experience working with large datasets and high-performance computing (HPC) environments Strong analytical and problem-solving skills in complex technical environments Ability to communicate effectively with both technical and non-technical stakeholders Comfortable working in collaborative, cross-functional teams within a fast-paced R&D environment Ability to learn complex topics quickly and translate research into practical solutions PhD in Computer Science, Mathematics, Statistics, Physics, or a related field (desirable) Experience deploying machine learning models to edge or embedded compute hardware (desirable) Experience with MLOps workflows, including continuous training, testing, and deployment pipelines (desirable) Experience with real-time systems, sensor data processing, or advanced signal processing (desirable) Exposure to quantum technologies, quantum information science, or quantum machine learning (desirable) Responsibilities: Develop and implement custom machine learning models for signal processing, sensor fusion, and system optimisation Design models for applications such as noise suppression, drift compensation, anomaly detection, and adaptive calibration Build and maintain robust data pipelines to process high-dimensional experimental and time-series datasets Train, validate, and optimise machine learning models using modern Python-based frameworks Integrate ML inference into real-time or near-real-time control environments Stay up to date with the latest developments in machine learning and sensor fusion techniques Interpret and communicate cutting-edge research in both theory and experiment with internal teams Contribute to the wider scientific community through publications, conferences, or technical collaboration Support and mentor colleagues, contributing to a collaborative research and engineering environment Technologies: Embedded Hardware Support Machine Learning PyTorch Python Sensor Fusion pandas More: We are an innovative technology company based in Oxfordshire, offering a permanent hybrid role for a Machine Learning Engineer (MLOps). This position provides the unique opportunity to work at the forefront of advanced computing and emerging technologies, developing ML-driven applications that enhance next-generation technology. Our team is passionate about solving complex scientific and engineering challenges, supporting a collaborative environment where you can contribute and grow. last updated 11 week of 2026