This role involves analyzing large-scale security telemetry, threat intelligence feeds, and detection data to uncover patterns and support strategic initiatives. You will work cross-functionally with product and engineering teams to transform raw security data into actionable insights, using tools like SQL, Python, and Logscale.
This role involves analyzing large-scale security telemetry, threat intelligence feeds, and detection data to uncover patterns and support strategic initiatives. You will work cross-functionally with product and engineering teams to transform raw data into actionable insights, design dashboards, and maintain data pipelines.
Conduct cutting-edge research in reinforcement learning and large language models to advance general intelligence in AI systems. Collaborate on developing models with enhanced memory and task capabilities, publish high-impact work, and contribute open-source code to ensure reproducibility. Work within a leading AI research team focused on long-term breakthroughs in intelligent machines.
This role involves building and deploying AI-driven simulation applications that solve complex engineering problems across industries like aerospace, energy, and semiconductors. You'll work closely with customers, data scientists, and ML engineers to design end-to-end tools that integrate physics AI models into real-world engineering workflows. The position emphasizes rapid prototyping, full-stack development, and translating cross-industry challenges into scalable software solutions.
This role involves managing a team of Technical Deployment Leads (TDLs) in the Financial Services sector, ensuring high-quality delivery of AI solutions, and building strong relationships with executive stakeholders. Responsibilities include hiring, developing team members, managing customer engagements, and setting technical and operational standards.
This role involves shaping the direction of Darktrace's Network Detection and Response (NDR) product by aligning customer needs with technical development. The Product Manager will work closely with R&D, marketing, and go-to-market teams to prioritise features, ensure effective product messaging, and support customer adoption. A strong understanding of cybersecurity, particularly in network security and real-world NDR deployment, is essential for success in this position.
Build and maintain foundational systems for AI safety, oversight, and intervention mechanisms, focusing on detecting unwanted model behaviors and preventing misuse. Develop infrastructure for data management, evaluation systems, and tooling for human and agentic review while ensuring high operational reliability at scale. Work closely with cross-functional teams to implement robust, multi-layered defenses in a safety-first AI environment.
Build and maintain scalable backend systems powering AI voice and creative tools used by millions. Work across platform, product, and infrastructure to integrate cutting-edge AI models, improve developer APIs, and strengthen cloud-native systems. Collaborate with frontend, growth, and sales teams to deliver intuitive, secure, and high-performance solutions.
Build and maintain front-end and back-end components for AI-powered voice, creative, and developer platforms used by millions. Work with lean, autonomous teams to deliver end-to-end features, improve UX, and integrate cutting-edge AI models. Collaborate across engineering, growth, and sales to solve customer and internal workflow challenges.
This role involves driving new business sales in cybersecurity across Central and Eastern Europe, owning the full sales cycle from prospecting to closing. You'll engage with enterprise clients, present AI-powered threat defense solutions to CISOs and security teams, and collaborate with technical experts and SDRs. The position supports remote work from Poland or London and emphasizes relationship-building in a high-growth, tech-driven environment.
A Senior Machine Learning Engineer will lead the deployment of AI models into production environments for engineering and physics simulations, working closely with customers and cross-functional teams. The role involves building scalable ML pipelines, mentoring engineers, and traveling to client sites globally. The position operates at the intersection of data science and software engineering, focusing on real-world impact in advanced industries.
Design and experiment with novel Transformer and GNN architectures to build a unified foundation model that understands relational databases and heterogeneous graphs. Work across the full ML lifecycle—from architecture design to inference acceleration—on real-world applications like fraud detection, forecasting, and recommendation systems. Collaborate with researchers and engineers to push the boundaries of relational reasoning in enterprise AI.
Build and deploy end-to-end AI applications for public sector clients, leveraging cutting-edge models and open-source tools. Collaborate with cross-functional teams to create high-quality training datasets and evaluation frameworks. Engage in customer projects with occasional travel, focusing on real-world AI impact at scale.
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 working directly with quantitative investment and trading firms to apply OpenAI’s models and Codex to their research and development workflows. Responsibilities include identifying valuable opportunities, building and deploying AI systems, and guiding technical decisions to ensure production readiness and customer impact.
