This internship involves researching and developing GPU-accelerated techniques for deep learning, machine learning, and AI workloads. You will collaborate with experts to optimize complex algorithms, publish findings, and influence the design of next-generation hardware and software.
This internship involves researching and developing GPU-accelerated techniques for deep learning, machine learning, and AI workloads. You will collaborate with technical experts to optimize complex algorithms and contribute to the design of next-generation hardware and software at NVIDIA.
Lead the end-to-end data strategy for AI-driven autonomous vehicles, focusing on intelligent data discovery, curation, and enrichment from diverse real-world sources. Build and scale a global data organisation to accelerate model performance across multiple geographies and vehicle platforms. Drive the learning loop from real-world signals to model improvement, prioritising rare and safety-critical scenarios.
This role involves developing and optimizing the software stack for Wayve's autonomous driving vehicles, focusing on performance, latency, and system efficiency. You will work closely with multiple teams to identify and resolve bottlenecks, implement profiling tools, and enhance the overall system performance.
This role involves leading the design and implementation of advanced algorithms for intelligent systems in defence and security contexts, with a focus on machine learning, AI, and sensor processing. You'll act as technical architect on complex projects, mentor engineers, and contribute to client-facing proposals and sales efforts. The position requires security clearance and combines hands-on development with strategic technical leadership in multidisciplinary teams.
This role involves leading the design and development of advanced digital electronics and FPGA-based systems for cutting-edge communications technologies, including Low Earth Orbit Satellites and High-Altitude Platform Systems. The engineer will work on high-speed board-level design, FPGA verification, and system architecture within small, interdisciplinary teams. Projects are innovative and varied, spanning telecommunications, healthcare, and sustainable energy, with access to in-house prototyping and testing facilities.
This role involves leading and scaling a team of AI/ML professionals, developing executive relationships with key EMEA customers, and driving strategic initiatives. The role requires deep technical expertise in ML, GenAI, and data science, as well as experience in managing and growing high-performing teams.
This role involves serving as a technical advisor to enterprise customers adopting Claude, designing scalable AI architectures, and guiding integration of Anthropic's LLMs into existing technology stacks. The position bridges technical and business stakeholders, creating evaluation frameworks and delivering tailored technical content. Collaboration with sales, product, and engineering teams is central to driving successful customer deployments.
Acts as the post-sale technical lead for strategic customers, driving adoption and successful implementation of Databricks workloads. Focuses on technical accountability, cross-team orchestration, and execution planning across use cases, from onboarding to production. Engages with stakeholders at all levels to ensure healthy consumption and return on investment of the Databricks platform.
This role involves leading technical engagements in data architecture and strategy, building and deploying machine learning models, and staying up-to-date with the latest trends in GenAI. You will manage a small team and act as the technical expert in machine learning and large language models.
Drive land-and-expand sales strategies for enterprise clients with over 10,000 employees, focusing on AI-powered video solutions. Collaborate with Customer Success to ensure adoption, retention, and growth. Operate in a high-growth, value-driven SaaS environment using methodological sales frameworks.
This role involves conducting original quantitative research to develop statistical and mathematical models for trading, using large, noisy datasets and proprietary infrastructure processing billions of market events daily. The scientist will translate research into production code, peer-review ideas, and explore unconventional approaches with potential investment value. The position emphasizes deep mathematical problem-solving, programming rigor, and collaboration in a research-driven, intellectually autonomous environment.
This role involves developing patient-specific models using machine learning to predict disease states and treatment responses for cardiovascular digital twins. The postholder will work with multimodal clinical, physiological, imaging, and sensor data to enhance precision treatment.
The Data Scientist will develop tools and workflows to automate data extraction, processing, and analysis, build and maintain data pipelines, and generate meaningful insights and visualisations from complex datasets. They will also apply statistical and machine learning techniques to support product development and present insights to stakeholders.
Develop and test alpha-generating strategies for systematic equity portfolios using statistical techniques, machine learning, and large-scale data analysis. Work closely with portfolio managers to transition research into live trading, building predictive models and robust research infrastructure in Python. Focus on rigorous backtesting, signal validation, and collaborative research in a high-impact environment.
