Jobs at Dyna Robotics

Own end-to-end video production for robotics: shoot demos, interviews, events and behind-the-scenes; edit footage into short-form social, product, research, and recruiting content with high visual quality, pacing, sound, color, and storytelling.

Own the data engine and deployment platform that turns field robot behavior into training signal. Define capture, labeling schema, quality standards, annotation pipelines, observability, and tooling for researchers, engineers, operators, and customers. Improve operator and customer experiences, instrument fleets, audit labels, and spend time on-site to observe failures and drive product decisions.

Lead high-volume, full-cycle recruiting for operations roles (operators, teleoperators, technicians). Source at scale, coordinate screens/interviews/onboarding, partner with operations leaders to forecast headcount, track and improve hiring metrics, and streamline ATS workflows and automation to maintain fast, high-quality hiring while delivering a positive candidate experience.

Own hardware product strategy for next-generation robots: define requirements for mobility, sensing, and end-effectors; translate field learnings into specs; drive delivery through DVT to production; prioritize reliability, serviceability, and tradeoffs across cost, capability, and timeline while aligning cross-functional teams.

Lead QA function across Dyna's robotics stack, managing a team, developing automated test frameworks, and ensuring hardware behavior validation.

The Marketing and Communications Lead will shape Dyna's narrative, manage PR, lead content strategy, and attract talent while enhancing brand visibility in the robotics and AI sectors.

Own day-to-day annotation operations: reporting, Encord pipeline management, throughput and quality metrics, automation of runbooks, people management (hiring, payroll, performance), and vendor/partner coordination to keep labeling projects flowing predictably.

Manage end-to-end onboarding and offboarding, process employee lifecycle changes, maintain HRIS records, administer required trainings, and serve as primary employee contact for policies, benefits, payroll, and people-related questions. Improve workflows and internal resources to scale operations.

The Research Engineer/Scientist will develop AI models for robotic manipulation, design learning algorithms, analyze results, and collaborate with cross-functional teams to enhance performance.

The Deployment Success Manager will oversee customer deployments, manage operational execution on-site, and ensure stakeholder communication, tracking project timelines and addressing any operational challenges that arise during deployment.

The AI Data Strategist role focuses on defining data requirements to drive model improvement across robotic platforms, emphasizing data collection priorities, evaluation frameworks, and lifecycle observability.

Develop and lead software for robotic systems, focusing on control, sensing, teleoperation, and integration with AI and hardware teams.

Lead and build a blended engineering organization across hardware, software, AI systems, and deployment. Hire and retain teams, set operating cadence, remove bottlenecks, drive cross-functional initiatives from research to field validation, and align vision to execution for reliable customer deployments.

Build facility-scale simulated worlds and pipelines for loco-manipulation: real-to-sim reconstruction, procedural scene generation, synthetic data for joint base+arm policies, photorealistic rendering to close sim-to-real gaps, and evaluation benchmarks. Collaborate with AI Research and Data Ops to prioritize simulated data and feed real-world failure modes into simulation.

This role involves leading business operations, addressing operational bottlenecks, supporting customer deployments, and managing various analytical tasks in a high-growth startup.

Deploy and maintain on-site robotics systems: network bring-up, inference server provisioning, incident response, cross-stack debugging (Linux, containers, GPUs, hardware), customer coordination, runbook and automation creation, and reporting issues back to engineering.

Design and build data systems for robotic intelligent workflows, focusing on automation, signal extraction from multimodal data, and ML model evaluation.

Accepting applications for a limited number of research-focused internships in robotics. Seeking candidates passionate about the intersection of geometry and robotics; values problem-solving, grit, technical rigor, and diversity. Open to applicants at all levels.

Annotate data on robot tasks to improve AI performance. Maintain data integrity, apply guidelines, and use pre-annotation tools for quality checks.

Short-term (60-day) temporary role to collect high-quality data by following SOPs. Set up workstations and equipment, perform repetitive collection tasks, report issues, maintain cleanliness, meet productivity and quality targets, and accept coaching to improve performance.