As a Senior AI Engineer at PoliceAI, you will lead the design, development, and deployment of AI-enabled products, translating policing needs into technical solutions. You will work with multidisciplinary teams to build secure, maintainable, and scalable services, and support the testing, evaluation, and validation of AI products.
As Head of AI, you will lead the development and implementation of AI strategies, governance, and capabilities at LPPA, a leading pension administration company. You will work closely with the CTO and executive team to identify and deliver AI opportunities that enhance operational efficiency, service quality, and member outcomes. Key responsibilities include building the AI team, establishing governance frameworks, and fostering AI adoption across the organization.
This role involves designing, developing, and deploying secure AI and ML solutions for autonomous and mission-critical systems. Responsibilities include building machine learning models, supporting autonomous capabilities with ROS 2, and ensuring adherence to Responsible AI and safety standards.
The role involves contributing to world-leading AI research and teaching at the University of Bristol. Responsibilities include publishing in top academic venues, applying for external funding, and delivering high-quality undergraduate and postgraduate courses in AI and Computer Science.
This role involves collaborating with teams to secure AI and Machine Learning solutions, conducting threat modelling, and ensuring compliance with security standards. The position offers exposure to cutting-edge AI technologies and a dynamic, collaborative environment.
The Data Scientist will develop and implement machine learning models to solve business problems, analyse large datasets for actionable insights, and collaborate with technical and business stakeholders to deliver data-driven solutions. The role involves preparing, cleaning, and transforming data, as well as evaluating and monitoring models for accuracy and reliability.
Develop pre-silicon software models of AI accelerator hardware to support architecture design, performance analysis, and early software development. Work collaboratively across hardware, software, and machine learning teams using a co-design methodology. Contribute to the development of high-performance computing solutions for large language models.
Develop pre-silicon software models for AI accelerator hardware to support architecture design, performance evaluation, and early software development. Work closely with hardware, software, and ML teams in a collaborative co-design environment. Models will inform product design and enable verification prior to fabrication.
The Data Scientist role involves solving maritime and security-based problems using machine learning and data science techniques. Responsibilities include developing and evaluating ML models for anomaly detection, track pattern recognition, and integrating these models into user-facing features. The role also involves collaborating with developers and infrastructure engineers to build scalable data pipelines and contribute to feature development.
As a Data Scientist at SRT Marine Systems, you will work on developing and evaluating ML models for maritime and security-based problems, including detection, classification, and anomaly detection in time series and image/video data. You will collaborate with developers and engineers to integrate these models into user-facing features and build scalable data pipelines.
Design and build core platform systems to support technical research on AI-related chemical and biological risks, translating ambiguous research needs into scalable, maintainable software solutions. Work within a multidisciplinary team to develop LLM-based agent systems, evaluation frameworks, and shared infrastructure while mentoring engineers and shaping technical direction. Operate in a high-impact environment with direct influence on AI policy and global governance.
The role involves translating research into commercial solutions, developing physics-informed models for ship performance, and integrating these into NeuralShipper, a platform for automated vessel design. The engineer will work on multidisciplinary optimization and wind-assisted propulsion systems, collaborating with industry stakeholders.
As a Machine Learning Engineer in Delivery, you will work closely with customers and internal teams to design, build, and test reliable, scalable ML pipelines. You will deploy production-grade tools, manipulate 3D data, and integrate models with simulations, traveling to customer sites for on-site collaboration.
Build and improve the AI engine powering interactive roleplay training with AI avatars, focusing on real-time performance scoring, feedback generation, and dynamic response logic. Work on applied machine learning models integrated into a product-driven environment, collaborating closely with engineering and product teams to enhance learning-by-doing experiences. The role emphasizes fast iteration and delivering tangible impact through scalable AI systems.
Develop and deploy scalable machine learning systems integrated with high-fidelity physics simulations, working directly with customers and engineering teams to solve real-world industrial challenges. Focus on building reliable data pipelines, manipulating 3D point-cloud and mesh data, and translating research into production-grade tools. The role involves significant customer collaboration, on-site problem solving, and travel across multiple regions.
Develop and deploy production-grade machine learning systems for high-impact clients, particularly in the defence sector. Work across the full ML lifecycle, from scalable architecture design to operationalisation, using cloud platforms and containerisation tools. Collaborate with cross-functional teams to deliver ethical, reliable AI solutions in real-world environments.
This role involves developing an AI platform to generate and predict properties of novel peptide sequences, working closely with AstraZeneca and Queen Mary University of London. The position is based at AstraZeneca's Discovery Centre in Cambridge, with periodic travel to DERI for research and training.
