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.
Analyze end-to-end performance of large-scale AI workloads across compute, network, storage, and software stacks. Design performance studies, diagnose bottlenecks, and deliver optimization plans in collaboration with deep learning and platform teams. Use profiling and data analysis to drive improvements in scalable DGX Cloud systems.
Analyze end-to-end performance of large-scale AI workloads across compute, network, storage, and software stacks. Design and execute performance studies to establish baselines, diagnose regressions, and quantify bottlenecks. Define evaluation methodologies and success metrics for AI workloads, using profiling and data analysis to drive optimization. Partner with deep learning engineers, platform teams, and GPU architects to validate and deliver performance improvements.
Develop and execute validation strategies for ADAS functions within Wayve’s AI Driver system, using simulation and real-world testing to ensure safety and performance. Define metrics, test coverage, and acceptance criteria in collaboration with cross-functional teams. Analyze results and drive validation processes from concept to implementation in a fast-paced, innovative 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.
This role involves developing and maintaining scalable data pipelines for single-cell multi-omics data, integrating transcriptomics, chromatin accessibility, proteomics, and imaging to build multimodal datasets for machine learning. The Senior Data Scientist will work closely with wet lab scientists and ML teams to design experiments, evaluate biological relevance of models, and drive insights into cellular decision-making. The position emphasizes advanced computational analysis, interdisciplinary collaboration, and the use of modern ML tooling in a high-impact drug discovery environment.
Develop and apply advanced machine learning models to DNA and genetic data to uncover associations between genetic variants and diseases. Collaborate with computational and experimental scientists to validate hypotheses and integrate ML into target discovery pipelines. Work on sequence modelling tasks such as variant interpretation, gene discovery, and regulatory mechanism analysis using large-scale genomic datasets.
This role involves building and optimizing the machine learning infrastructure that supports Anthropic’s reinforcement learning research. You'll work closely with researchers to improve training efficiency, debug performance bottlenecks, and develop tooling that accelerates model development. The position focuses on high-leverage platform improvements that scale across the entire research team.
This role involves designing and maintaining large-scale, performance-sensitive distributed systems that serve Claude to millions of users globally. The engineer will work across the full inference stack, building intelligent routing, autoscaling, and deployment systems for AI models running on diverse accelerators across multiple cloud platforms. The position emphasizes real-time system resilience, compute efficiency, and close collaboration with research teams to enable next-generation model development.
Design and engineer functional proteins using proprietary generative AI models, bridging machine learning and experimental validation teams. Analyze structural biology and sequence data to generate and refine protein designs, then collaborate closely with wet lab scientists to test and iterate on results. Contribute to model improvement, data systems, and scientific knowledge sharing in a high-impact synthetic biology environment.
This role involves developing and deploying machine learning and NLP models for intelligence data, working closely with end users in a multi-disciplinary team. Responsibilities include pattern detection, data matching, anomaly spotting, and building production-ready data and ML pipelines.
This role involves designing and implementing AI solutions to improve operational efficiency, defining LLM architecture, and building AI tools like assistants and workflow automation. You will work within an Azure cloud environment, collaborate with product teams, and act as a key partner to the Director of AI.
This role involves leading the Data Hub engineering team, driving the delivery of a modern enterprise data platform, and making key technical decisions. You'll mentor data engineering teams, consolidate legacy systems, and partner with business stakeholders to shape the future of data and AI at the company.
This role involves leading end-to-end data science projects to enhance customer personalisation for major retail clients like Tesco UK. You'll design and deploy machine learning solutions using large-scale transactional data, conduct A/B testing, and translate complex insights for both technical and business audiences. The role emphasizes innovation, collaboration with high-impact teams, and deploying scalable data products in a fast-paced environment.
This role involves leading complex, multi-team technical programmes within a fast-paced engineering environment, focusing on planning, alignment, and delivery. The Technical Programme Manager will drive cross-functional collaboration, optimise processes, and ensure engineering efforts are aligned with strategic objectives. What sets this role apart is its focus on outcome-driven delivery within a high-growth fintech building cloud-native core banking technology.
