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.
Develop and lead the technical architecture for LiDAR and cross-sensor 3D sensing systems, focusing on calibration, synchronisation, and motion compensation across diverse vehicles and environments. Design robust algorithms for sensor alignment and temporal registration using optimisation and state estimation techniques. Provide technical mentorship and drive production-grade deployment of 3D sensing pipelines across Wayve’s autonomous driving platform.
This role involves applying advanced data science and machine learning techniques to enhance cyber security. Responsibilities include developing threat detection models, designing analytical methods, building security knowledge graphs, and collaborating with security teams to productionize solutions.
Develop and optimize compilers for AI inference workloads on NVIDIA's next-generation GPUs, focusing on kernel generation, computational graph optimizations, and hardware-software co-design. Collaborate with cross-functional teams to advance compiler frameworks and enable high-performance AI deployment at scale. Work spans MLIR-based tooling, deep learning performance, and datacenter-scale optimization.
This role involves developing advanced compiler technologies for AI inference and training workloads, focusing on kernel generation and computational graph optimizations tailored to NVIDIA's GPUs. You'll work at the intersection of hardware and software, collaborating with experts to co-design future silicon and optimize datacenter-scale AI deployments. The position demands deep expertise in compiler design, MLIR, and performance optimization in high-performance computing environments.
A Machine Learning Engineer will collaborate with simulation engineers and customers to solve complex physics and engineering challenges using AI. The role involves building scalable ML pipelines, working with 3D point-cloud and mesh data, and translating R&D into deployable tools. Engineers will also travel to customer sites globally to implement solutions on-site, ensuring practical, impactful delivery across industries like aerospace, energy, and semiconductors.
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.
Design and build LLM-powered agentic workflows that help generate testable therapeutic hypotheses for rare diseases by reasoning over scientific data, knowledge graphs, and proprietary methods. Collaborate closely with drug discovery scientists and engineers to translate real-world problems into reliable, production-grade agent systems. Work within an existing agentic framework to enhance and scale AI-driven decision-making in drug discovery.
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 hands-on development of machine learning and language model workflows, integrating with various providers, and building robust retrieval and evaluation systems. You will work on LangGraph, LangChain, and RAG pipelines, focusing on cost, latency, and auditability.
Design and build proactive, human-centred agentic systems that reason, plan, and act across domains like biotech, robotics, and AI. Develop full-stack architectures from edge reasoning to cloud deployment, integrating multimodal sensing and persistent memory. Work in agile, cross-disciplinary teams to rapidly prototype and productionise breakthrough systems for high-impact clients.
This role involves owning the end-to-end ML compilation pipeline for Wayve's autonomous driving technology, working with NVIDIA TensorRT and Qualcomm QNN. Responsibilities include designing compiler passes, integrating with vendor toolchains, and ensuring accuracy and latency requirements are met across various target platforms.
This role involves designing and managing enterprise AI platforms, intelligent agents, and automation workflows across cloud and on-premise environments. The engineer will build scalable AI architectures, develop RAG applications and multi-agent systems, integrate with business systems like Microsoft 365, and ensure solutions are secure, compliant, and performant. A strong focus is placed on responsible AI, governance, and translating technical capabilities for non-technical stakeholders.
This role involves developing and deploying machine learning and NLP models for intelligence data, working closely with end users in a small, multi-disciplinary agile team. Responsibilities include pattern detection, data matching, anomaly spotting, and building production-ready ML pipelines and dashboards.
You will design and develop cutting-edge agentic AI systems, build LLM-powered applications, and contribute to the architecture of a proprietary AI platform. The role involves close collaboration with product and engineering teams to embed AI into real-world business processes, with a focus on innovation and greenfield development.
