As a Solutions Architect, you will lead technical discovery and build reference architectures for enterprise-ready agentic AI products on the NVIDIA stack. You will collaborate with partners to develop proofs of concept, optimize workloads, and create reusable assets like benchmark reports and playbooks.
As a Solutions Architect, you will lead technical discovery and build reference architectures for AI application wrappers, orchestrating agents, and specialized workflows using NVIDIA's stack. You will work closely with partners to develop enterprise-ready agentic AI products, optimize workloads, and create reusable enablement assets.
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.
Design and build scalable cloud-based detection systems that process billions of events daily to identify sophisticated threats across multi-cloud environments. Work closely with security researchers to translate threat intelligence into automated, real-time detection capabilities using distributed systems and data engineering techniques. Develop and optimize components like custom query languages, event orchestration, and correlation engines within a modular, AI-native security platform.
Work on high-impact AI evaluation projects by designing domain-specific problems and datasets to assess advanced generative models. Collaborate with leading researchers and contribute to technical reports and publications in applied AI. Engage in flexible, interdisciplinary research with a global network of experts while using Python, Java, or other programming languages to improve model reasoning and performance.
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.
This role involves a 4-month, full-time research fellowship focused on ML systems and performance, with mentorship from Anthropic researchers. Fellows will work on empirical projects using external infrastructure to build scalable ML systems, debug training processes, and support high-performance computing environments. The program emphasizes collaboration, rapid implementation, and producing public research outputs such as papers.
Engage in empirical research on AI's economic and societal impacts, supported by mentorship from Anthropic researchers. Work on a project using external data and tools to produce a public output such as a paper, with opportunities to contribute to policy-relevant insights. Collaborate within a multidisciplinary team focused on AI safety and societal resilience.
This role involves delivering AI solutions for international public-sector customers, working closely with government agencies and technical teams to implement and scale GenAI applications. Responsibilities include hands-on technical implementation, strategic guidance, and building relationships with stakeholders.
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.
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.
This role involves deploying, tuning, and managing multi-rack GPU clusters and high-performance networks, ensuring the smooth operation of AI systems from hardware to the orchestration layer. You will work closely with researchers and engineers to optimize system performance and support a mission-led, not-for-profit AI organization.
This role involves deploying, tuning, and managing multi-rack GPU clusters and high-performance networks, working closely with researchers and engineers to optimize system performance. The position is unique in its hands-on approach to both hardware and software layers, supporting a mission-led AI organization that values collaboration and professional growth.
Design and optimize large-scale AI/ML infrastructure for biotech research, focusing on GPU/TPU systems, Kubernetes orchestration, and inference platform reliability. Build robust monitoring, CI/CD, and job scheduling systems to support high-throughput model serving and digital biology breakthroughs.
This role involves collaborating with the open-source community, implementing support for new AI models, scaling proxy infrastructure, and designing custom infrastructure for research projects. The team focuses on building tools and infrastructure for AI security and evaluation, working closely with researchers and government entities.
