Future Tech Jobs
Future Tech Jobs
Develop automated tools for large-scale data analysis, vulnerability research, and exploit development. Investigate 0-day and n-day vulnerabilities by analyzing patches, malware, and system logs. Collaborate across teams to support threat intelligence and publish findings in blogs or conferences.
Conducts advanced vulnerability research and exploit development, analyzing patches and malicious artifacts to identify 0-day and n-day vulnerabilities. Develops automated tools for large-scale data analysis and collaborates across teams to publish findings and support threat intelligence efforts. Focuses on reverse engineering, proof-of-concept creation, and rapid response to emerging threats.
Provide legal guidance across the product lifecycle for an AI video platform, focusing on AI, IP, privacy, and compliance. Advise cross-functional teams on responsible innovation, draft scalable legal frameworks, and support governance for privacy and AI. Work independently to balance legal risk with business objectives in a fast-paced tech environment.
Design and optimize GPU communication kernels for large-scale AI systems, focusing on low-level performance, memory efficiency, and integration with high-speed networking. Collaborate across hardware, software, and AI teams to co-develop GPU-aware communication primitives and programming models. Profile and tune end-to-end performance across compute, memory, and network boundaries to enable next-generation AI workloads.
Design and optimize GPU communication kernels for large-scale AI systems, focusing on collective and point-to-point operations. Work at the intersection of GPU architecture and networking, co-designing communication strategies with hardware and software teams. Develop low-level, GPU-resident primitives and tune performance across compute, memory, and network layers.
Design and optimize GPU communication kernels for large-scale AI systems, focusing on low-level performance tuning and co-design with hardware. Develop GPU-resident communication primitives and collaborate across teams to align networking strategies with GPU execution patterns. Work on foundational software enabling next-generation AI workloads with a focus on latency, efficiency, and scalability.
Design and optimize GPU communication kernels for large-scale AI systems, focusing on low-level GPU architecture and performance tuning. Collaborate with hardware and AI teams to co-develop communication strategies and programming models that align with GPU execution patterns. Profile and improve end-to-end performance of GPU-resident data movement across distributed accelerators.
Design and evolve scalable software systems for distributed AI training and inference, focusing on communication efficiency, runtime performance, and system-level integration across GPUs, DPUs, and interconnects. Develop next-generation capabilities in libraries like NCCL, UCX, and UCC, and collaborate with AI framework and hardware teams to optimize end-to-end performance at scale. Drive innovation in AI-specific protocol layers and co-designed solutions for large-scale AI workloads.
Design and evolve scalable software architectures for distributed AI training and inference, focusing on communication efficiency, runtime systems, and hardware-software co-design across GPUs, DPUs, and interconnects. Develop and optimize libraries like NCCL, UCX, and UCC for frontier AI workloads. Collaborate with AI framework and platform teams to improve end-to-end performance and enable next-generation AI infrastructure at scale.
A Research Scientist will focus on applying Large Language Models to drug discovery challenges, developing novel ML techniques and models that integrate with biological and chemical data. The role involves close collaboration with interdisciplinary teams of scientists and engineers to advance AI-driven drug design. Work includes model development, experimentation, and scaling frameworks for predictive applications in a fast-paced research environment.
A Research Scientist in machine learning will develop novel deep learning models and algorithms to accelerate drug discovery, working in an interdisciplinary team of scientists and engineers. The role involves designing architectures, training models, and applying ML to complex biological and chemical problems, with opportunities to lead projects and mentor others depending on experience.
This role involves deploying and optimising CrowdStrike’s AI-powered threat detection and response capabilities on the Falcon platform. The consultant will configure machine learning models, develop automation playbooks, integrate AI workflows with existing security tools, and provide technical guidance to customers and internal teams. The position requires deep expertise in AI/ML applications for cybersecurity, scripting with Falcon APIs, and troubleshooting across enterprise environments.
This role involves deploying and optimising CrowdStrike’s AI-powered threat detection and response capabilities for enterprise customers. The consultant will configure machine learning models, develop automation playbooks, troubleshoot AI-driven alerts, and integrate Falcon’s AI features into existing security workflows. A strong focus is placed on enhancing detection efficacy, reducing false positives, and leading AI skills development within the services team.
This role involves deploying and optimizing CrowdStrike’s AI-powered threat detection and response capabilities for enterprise customers. The consultant will configure machine learning models, develop automation playbooks, and troubleshoot AI-driven security workflows while providing technical leadership and customer support. The position emphasizes hands-on implementation, AI integration with existing security tools, and enhancing detection efficacy through advanced scripting and Falcon API utilization.
This role involves leading the technical aspects of an interdisciplinary research project evaluating AI chatbot responses to scenarios of coercive control and non-physical domestic abuse. The postholder will design and implement a reproducible evaluation framework for large language models, develop automated tools for data collection and analysis, and collaborate with experts in criminology and clinical practice. The work aims to generate evidence for policy and responsible AI development, with a strong focus on real-world safeguarding concerns.
