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.
Generates and qualifies leads for the sales team by engaging prospects via outbound campaigns and managing inbound inquiries. Focuses on the SMB/Corporate segment using CRM tools like Salesforce to schedule demos and build pipelines. Emphasizes creative outreach through email and social media to drive sales development.
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.
Lead client service delivery for Synthesia's AI video platform, coordinating design projects and ensuring clients achieve maximum value. Bridge internal teams and external stakeholders to streamline multimedia content production and improve processes. Focus on scalable solutions, project execution, and client satisfaction in a fast-growing AI environment.
This role involves generating and qualifying sales leads for Synthesia through inbound and outbound outreach, using phone, email, and social channels. The candidate will work closely with marketing and sales teams to convert interest into opportunities, with a strong focus on German-speaking markets. Success requires proactive lead mapping, cold outreach, and seamless handoff to account executives in a fast-paced AI startup environment.
Design and govern software architecture and CI/CD pipelines for safety-critical autonomous and robotic systems, integrating control, computer vision, sensor fusion, and simulation platforms. Support system integration and field trials with military users while ensuring scalable compliance with defence standards. Work in a hybrid setup with flexible hours and early Friday finishes.
The role involves curating and processing multilingual humanities data, pre-training and fine-tuning large language models, and developing evaluation benchmarks. You will work closely with subject specialists and contribute to open-source research and publications.
This role involves designing and prototyping generative machine learning models for protein design, with a strong focus on real-world biological applications. The scientist will build and evaluate models, collaborate across interdisciplinary teams, and iterate based on wet lab feedback. A significant emphasis is placed on high-performance code, scalable data pipelines, and staying current with advances in ML and synthetic biology.
This role involves developing and prototyping generative machine learning models for protein design, with a strong focus on real-world biological applications. You'll work closely with biologists and engineers to build scalable data pipelines, optimize model performance, and iterate based on wet lab feedback. The position emphasizes research excellence, production-grade code, and rapid experimentation in a cross-disciplinary environment.
Build and scale next-generation world model architectures to generate high-fidelity synthetic data for autonomous driving systems. Bridge ML research and engineering by optimizing generative models, ensuring training-grade video output, and integrating synthetic data into real-world training pipelines. Work across GPU-scale infrastructure, 3D geometry, and multi-sensor simulation to accelerate development across new vehicle platforms and safety-critical scenarios.
An Applied AI Engineer will work directly with enterprise customers to design, build, and deploy AI systems that solve real-world business problems. The role involves hands-on coding, system integration, and technical leadership to guide AI solutions from prototype to production, with a focus on reliability, safety, and measurable impact. The position requires deep technical expertise and strong collaboration with both customer teams and internal OpenAI groups.
This role involves partnering with engineering teams to design and deploy AI-powered software development workflows using Codex, transforming how organizations plan, code, test, and deliver software. The engineer will build prototypes, integrations, and evaluation systems—often using Codex in their own development—while guiding customers from experimentation to scaled production adoption. The position emphasizes technical leadership, hands-on coding, and translating real-world deployment insights into product and model improvements.
Lead the development and execution of translational medicine strategies for oncology programs, integrating AI-driven insights to advance drug discovery from preclinical to clinical stages. Serve as a cancer biology expert, guiding biomarker and companion diagnostic development while collaborating across multidisciplinary teams. Shape clinical trial design and regulatory submissions with a focus on mechanism of action, drug resistance, and novel therapeutic combinations.
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.
This role involves building and managing datasets and evaluation systems for AI safety, translating safety policies into actionable data criteria, and creating scalable processes for data collection, labelling, and model assessment. The Data Scientist will work across policy, research, and engineering to ensure models are evaluated using real-world data and robust quality standards. A strong focus is placed on developing reproducible pipelines and operationalising safety frameworks in a fast-moving AI environment.
