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.
A Research Scientist role focused on applying Large Language Models to drug discovery challenges, working within an interdisciplinary team of AI and life sciences experts. The position involves developing novel LLM-driven methods, refining models for biological and medical applications, and collaborating across scientific domains. The role requires deep technical expertise in LLMs and a strong foundation in machine learning and computational science.
A Research Scientist in Machine Learning will develop novel deep learning models and algorithms to accelerate drug discovery, working in a cross-disciplinary environment with scientists and engineers. The role involves designing architectures, training models, and applying cutting-edge ML techniques to biological and chemical problems, with opportunities to lead projects and mentor others depending on experience.
This role involves building and scaling generative and predictive machine learning models for cellular behaviour using multi-omic and interventional biological data. The engineer will implement large neural networks, optimise distributed training and inference pipelines, and collaborate closely with ML scientists and biologists to translate research into production-grade systems. Work focuses on robust infrastructure development, performance optimisation, and integrating cutting-edge ML tooling within an interdisciplinary team.
This role involves leading and scaling a team of AI/ML professionals, developing executive relationships with key EMEA customers, and driving strategic initiatives. The role requires deep technical expertise in ML, GenAI, and data science, as well as experience in managing and growing high-performing teams.
This role involves developing generative and predictive models of cellular behaviour using high-content imaging data such as cell painting and brightfield assays. The Senior Data Scientist will curate imaging datasets, design evaluation frameworks to distinguish biological signal from artefact, interpret foundation model outputs, and collaborate closely with wet lab teams to ensure data quality and analytical tractability. The position is embedded in a multidisciplinary environment integrating machine learning, single-cell multi-omics, and functional assays to advance drug discovery.
This role involves leading and improving the training and performance of Gaia, Wayve's world model for autonomous driving. Responsibilities include fine-tuning the model, enhancing its stability and coherence, and collaborating with research and engineering teams to drive measurable impact.
This role involves developing high-fidelity computational plasma models for semiconductor manufacturing processes such as etching and deposition, integrating them with AI-driven simulation tools. The engineer will work directly with customers on-site, validate models against real-world data, and collaborate with data science and ML teams to deliver actionable engineering solutions. The position emphasizes technical ownership, cross-functional collaboration, and global travel to support customer implementations.
This role involves developing and evaluating AI and machine learning solutions, particularly using GCP, LLMs, and RAG. You will work closely with project managers and developers to deliver scalable and well-documented solutions, gather business and technical requirements, and contribute to application design and troubleshooting.
This role involves building and deploying machine learning models to solve business challenges in financial services, collaborating with data engineering and analytics teams to create reproducible pipelines, and translating complex data into actionable insights. The position offers the opportunity to shape the data science practice within an established company.
This role involves applying statistical methods for anomaly detection, transforming raw telemetry into actionable insights, and working with mobile app KPIs. You will contribute to an established architecture, own features end-to-end, and communicate data-driven findings to leadership and non-technical stakeholders.
As a Research Scientist, you will work on the cutting edge of generative AI, focusing on interactive avatars that can engage in natural, real-time conversations. Your responsibilities will include advancing the state of the art in dyadic interaction modeling, post-training multimodal models, and building robust evaluation frameworks.
The Senior Data Scientist will maintain and troubleshoot live machine learning models, monitor revenue and data integrity, and handle time-sensitive regulatory requests. They will work closely with cross-functional teams to ensure operational stability and drive data-driven decisions.
As a Data Scientist at SRT Marine Systems, you will work on developing and evaluating ML models for maritime and security-based problems, including anomaly detection and track pattern recognition. You will collaborate with developers and engineers to integrate these models into user-facing features and build scalable data pipelines.
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 model outputs into user-facing features. The role is part of a collaborative, data-orientated team focused on enhancing civil defence security through advanced automated security infrastructures.
This role involves designing and prototyping novel generative machine learning models for protein design, with close collaboration between computational and experimental teams. The scientist will build scalable data pipelines, optimize deep learning models for performance, and iteratively refine models based on wet lab feedback. A strong emphasis is placed on code quality, interdisciplinary collaboration, and translating model outputs into real-world biological functions.
