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 delivering data engineering and analytics solutions for external clients, with a focus on financial services and regulatory compliance. The consultant will work on data platforms like Databricks, Snowflake, and Microsoft Fabric, supporting audit automation and advising on data governance and AI model validation. The position requires a versatile, client-facing technologist comfortable with travel and hybrid working.
This role involves building data pipelines, creating customer journey dashboards, and conducting deep-dive analyses to improve customer success metrics. You'll leverage Gen AI for automation and anomaly detection while supporting A/B testing and data-driven decision-making across digital and service domains. The position emphasizes cross-functional collaboration and storytelling to influence strategy.
Lead the design and deployment of scalable AI and generative AI solutions, including LLM-powered applications for enterprise search, document summarization, and conversational AI. Develop retrieval-augmented generation systems using vector databases and cloud platforms, while mentoring teams and shaping enterprise AI strategy. Work across data engineering and MLOps to deliver production-grade AI with measurable business impact.
This role involves deploying, managing, and validating high-performance storage infrastructure within AI Factory environments running on Linux. The engineer will act as a technical expert during customer engagements, from planning through implementation, while also contributing to system design, automation, and performance validation. Key responsibilities include troubleshooting, performance optimization, documentation, and providing feedback to internal teams to improve products and workflows.
This role involves owning full-solution validation, minimizing time to production, and ensuring Day 2 stability for large-scale GPU clusters. You will work closely with customers, partners, and cross-functional teams to architect, implement, and optimize Kubernetes-based platforms and HPC systems, providing hands-on technical leadership and consultative guidance.
This role involves rapid prototyping and experimentation with cutting-edge AI technologies such as large language models, AI agents, and intelligent automation to solve real business challenges in financial services. The engineer will build working solutions, run pilots with users, and validate emerging AI tools for enterprise scalability. Emphasis is on a hands-on, build-first approach within an agile innovation lab environment.
As a Customer Performance Analyst at Entrust, you will analyze customer performance data to identify trends, resolve issues, and improve product performance. You will work closely with cross-functional teams to provide evidence-based recommendations and ensure customer satisfaction.
This role involves leading legal technology projects with a focus on document automation and Generative AI, acting as a bridge between legal teams and technical experts. The consultant will configure workflows, manage vendor platforms, and drive adoption through training, all within a global legal services firm. What sets this role apart is its hands-on technical engagement with AI and low-code tools in a high-impact legal innovation context.
This role involves leading the technical development of a research platform that harmonizes data from multiple sources using NLP technologies. You will work within a multidisciplinary team to implement new features, maintain existing software, and ensure the platform meets commercial standards.
Design and build high-performance Java-based trading engines and real-time systems for algorithmic trading in equities. Develop algo strategies, liquidity-seeking logic, and real-time trading desktops using React. Work closely with trading desks and engineering teams to enhance electronic trading capabilities within a regulated sell-side environment.
This role involves building and maintaining scalable data pipelines, designing data models, and developing machine learning solutions to support AI initiatives and business intelligence. You will work closely with stakeholders to translate business challenges into analytical solutions, using tools like Microsoft Fabric, Databricks, and PySpark.
This role involves building and deploying predictive and statistical models, developing customer segmentation and churn models, and delivering forecasting and customer analytics solutions. You will work across the full Data Science lifecycle, from problem definition to deployment, and collaborate with analysts, engineers, and business stakeholders to present insights and recommendations.
This role involves developing and deploying machine learning models for financial market predictions, building AI systems to extract information from financial documents, and contributing to data infrastructure. The position requires a strong quantitative background and experience in machine learning, statistical modeling, and data engineering.
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 end-to-end ownership of existing analytics and production data science models for UK and Canadian markets, with a focus on revenue monitoring, partner performance, email campaigns, and experimentation. The Data Scientist will maintain and troubleshoot live systems rather than build new models, ensuring reliability and clear communication with cross-functional teams. The position requires strong operational discipline and technical maintenance of established pipelines and reporting.
