• Own the deployment, configuration, and ongoing management of Bobsled’s AI data agents for enterprise customers, acting as the primary technical point of contact for a small book of accounts. • Rapidly develop subject matter expertise in each customer’s data layer, context layer, and operational workflows. • Design, implement, and tune context ingestion, data pipeline integration, and agent orchestration to ensure high-performing, reliable AI deployments. • Write and ship production-grade code, customizing and extending Bobsled’s platform to meet customer-specific requirements. • Collaborate closely with customer stakeholders (technical and non-technical) to understand business objectives, untangle complex requirements, and translate them into actionable technical solutions. • Conduct rapid prototyping, iterative solution development, and high-touch troubleshooting directly in customer environments. • Monitor, evaluate, and improve the performance of deployed solutions, leveraging feedback loops to identify opportunities for enhancement and generalization. • Document best practices, reusable patterns, and deployment primitives, contributing to internal knowledge bases and future product abstractions. • Partner with Bobsled’s product and engineering teams to relay insights from the field, shaping platform evolution and customer success strategies.

• Investigating the latest and future NVIDIA GPU hardware architecture and programming models • Working on the frontier of AI by understanding advanced algorithms (like attention sinks and MoEs) and numerics (like block-scaled floating point) to identify new opportunities for optimization • Designing and implementing compiler technology using MLIR to optimize high-level kernel descriptions (written in Triton's Python DSL), with a focus on generating efficient, low-level GPU code • Engaging in a dynamic, iterative process of optimization—sometimes starting with the kernel, sometimes with the compiler—to find the most efficient path to peak performance • Collaborating with teams across NVIDIA, including hardware architects and the CUDA compiler team, to influence future products and ensure we are always operating at maximum efficiency

• Design, develop, and implement computer vision systems, including navigation systems for aerial applications. • Write clean, efficient, and well-documented code in C++ and Python. • Collaborate with cross-functional teams to design and test integrate robotic and vision systems. • Collaborate with external stakeholders, including customers to understand requirements, conduct tests and understand changes and improvements needed to be made. • Optimize system performance and ensure robust, reliable operation in diverse environments. • Debug and troubleshoot system issues to identify and implement effective solutions.

• Design, develop, and implement autonomy software for aerial autonomy, navigation, and real-time mapping. • Work with internal product teams to integrate new features and improve existing functionality. • Partner directly with customers and stakeholders, including in field testing and operational environments, to understand operational needs and deliver tailored solutions. • Improve and troubleshoot performance of deployed systems, providing rapid iteration in response to end-user feedback and on-site challenges. • Coordinate and execute field tests, demonstrations, and pilot programs in dynamic environments. • Serve as the technical liaison between product development and end-users, translating practical feedback into actionable roadmaps for the engineering org. • Champion best practices in code quality, security, and maintainability across the development lifecycle.