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Build and scale simulation infrastructure for robotic digital twins. Develop pipelines that convert lidar maps into simulation-ready environments, create reinforcement learning training environments, generate rare-event scenarios, model RGB, thermal, and lidar sensors, and measure and reduce sim-to-real gaps. The role also involves GPU-parallel simulation and collaboration with robotics, orchestration, reliability, and test infrastructure engineers.

Build and ship the Command Centre interface for monitoring robots, cameras, alerts, maps, and fleet tasks. Design and prototype operator workflows, test them with users, and implement production frontend code. Develop real-time, data-heavy experiences using React and TypeScript, integrate backend APIs and WebSockets/WebRTC, maintain a design system, and optimize accessibility and performance for mission-critical operations.

Serve as Laelaps AI’s first people hire, owning recruiting, hiring operations, technical sourcing, HR administration, onboarding, offboarding, policies, employee records, candidate and employee experience, and employer branding. Partner with founders and hiring managers to grow the Zurich team by 15–25 employees while maintaining a high hiring bar and humane, efficient processes.

Build and deploy real-time robot state estimation systems using sensor fusion across IMUs, cameras, LiDAR, GNSS, and odometry. Improve localization and odometry in challenging environments, integrate estimates with perception, planning, and control, investigate failures using logs and simulations, and develop repeatable evaluation workflows. Collaborate with autonomy and field engineers to improve reliable performance across robot platforms.

Train and evaluate reinforcement learning policies for locomotion and low-level actuator control in simulation and on physical legged robots. Apply sim-to-real techniques, domain randomization, reward design, and robustness methods across varied terrain, weather, and sensor conditions. Build reproducible experiment and evaluation workflows, transfer policies between robot embodiments, and use strong software engineering practices including version control and experiment tracking.

Develop and deploy dependable navigation and path-planning systems for ground mobile robots operating at real customer sites. Responsibilities include sensor integration, terrain and traversability estimation, obstacle avoidance, behavior prediction, planning under localization uncertainty, field debugging, simulation, and validation on physical robots across varied weather and environments. Collaborate with autonomy, application, backend, and field engineers to improve reliability and deliver new capabilities.

The Founder's Associate works directly with the founding team across go-to-market, operations, market research, fundraising support, and growth initiatives. Responsibilities include defining target customers, building prospect lists, running outreach, developing AI agent systems, monitoring tenders and grants, creating customer-facing materials, modeling growth and funnels, and maintaining CRM infrastructure. The role requires high autonomy, commercial judgment, technical affinity, and the ability to manage ambiguous, high-impact projects in a Zurich-based startup.

Own full-cycle enterprise B2B and public-sector sales as the first dedicated sales hire. Source pipeline, run discovery and demos, scope pilots, negotiate, close six-figure deals, maintain CRM hygiene, forecast accurately, and build the sales playbook. Partner with the CEO on strategy, pricing, positioning, and early deals, then coach and lead the future sales team. The role focuses on selling technical security and robotics solutions to enterprise, industrial, government, and defense customers.

Build and operate cloud and edge infrastructure connecting robot fleets to operator systems. Responsibilities include cloud networking and IAM, secure VPN and PKI connectivity, CI/CD, Kubernetes and K3s orchestration, infrastructure as code, fleet management, observability, developer tooling, and security hardening. The role supports cloud, on-premises, and potentially air-gapped deployments, with ownership of durable infrastructure foundations and developer experience.

Build and deploy production computer vision and machine learning systems for multi-camera robotics and surveillance. Responsibilities include cross-camera re-identification, object detection, multi-object tracking, vision-language model integration, real-time video streaming, edge optimization on Jetson hardware, data pipelines, model evaluation, and collaboration with robotics and software teams.