Software Engineer, Applications

Dyna Robotics builds general-purpose robots powered by a proprietary embodied AI foundation model with top-in-industry generalization and real-world performance. Already deployed with customers across multiple industries, our robots do commercial-grade work in the physical world. Our team comes from Google DeepMind, Meta, and Cruise, and we're backed by CRV, First Round, and other leading investors. As a Software Engineer, Applications, you’ll work across applied research on model stability, on-robot software, and the off-board systems and tooling that keep a fleet running. Many believe that as long as a robot is “smart” enough, deploying it is easy. At Dyna, we know the truth: the real world is wild, unpredictable, and unforgiving. Landing breakthrough AI research into the field takes deep investment in infrastructure and applied research. As we scale the number of deployed sites, the bottleneck is no longer whether a robot can perform a task once. It’s whether we can deploy, monitor, debug, and improve robots across many environments without every site becoming a one-off engineering project. Your job is to turn that messy, high-friction reality into durable engineering infrastructure. You’ll partner closely with our Operations team rather than selling to customers, with one goal: make deployment N+1 faster and more reliable than deployment N. This is a cross-domain role spanning applied research on model stability, on-robot software, and the off-board systems and tooling that keep a fleet running. This is a full-time, on-site position in Redwood City. What You’ll Do Deployment Platform: Build the deployment platform. Design and ship internal tools and systems for site bring-up, robot configuration, fleet monitoring, remote diagnostics, data capture, failure triage, deployment checklists, and operational dashboards. Operations Partnership: Partner with Operations. Embed with the Ops team to understand field reality, identify which failures matter most, and turn manual workflows into reliable software. Standardize how new sites are launched so each deployment compounds on the last. Research Feedback Loop: Close the loop with the model team. Build the pipelines that route useful data and failure cases from the fleet back to research, and make it easier to compare performance across different environments and tasks. Applied Research & Engineering: Participate in applied research focused on ensuring model-level stability and consistency when deploying complex AI models into unpredictable real-world environments. End-to-End Infrastructure Architecture: Design and build highly reliable infrastructure that bridges on-robot application software with large-scale off-board computing and cloud operations. Research-to-Field Bridge: Bridge research and reality. Act as the technical bridge between our core AI research teams and our deployment reality, translating complex lab research into robust, field-ready systems. Engineering Excellence: Champion rigorous testing, continuous integration, and scalable software practices that ensure our systems can handle the immense complexity of the physical world. What You’ll Bring Education: Bachelor’s degree or higher in Computer Science, Computer Engineering, Robotics, or a related field. Strong CS Foundations: Deep, first-principles understanding of systems architecture, software design patterns, and application-level development. You understand how systems work under the hood, not just how to string APIs together. The Experience: At least 3 years of professional experience as a versatile software engineer, with strong capabilities in both backend systems and broad application-level software. Python: Proficient in the Python ecosystem. Cross-Domain Software: Proven experience building robust, scalable software that spans multiple domains (e.g., bridging cloud backend services with edge devices, physical hardware, or complex data collection systems). Containers & Cloud: Experience with containerization, orchestration (Docker, Kubernetes), and cloud architecture (AWS, GCP, Azure). Adaptability: Highly adaptable and comfortable working across a varied tech stack. Communication: Strong cross-domain communication skills, with the ability to collaborate effectively with Operations, AI researchers, hardware engineers, and platform teams. Operational Mindset: Comfort with ambiguity, a deep interest in operational pain, and motivation to build systems that compound. You’re excited to work close to production robotics and turn heroic on-site effort into durable engineering. Passion for Robotics Infrastructure: Demonstrated passion for the intersection of AI research and wide-scale infrastructure, specifically for robotics or autonomous systems. Bonus Points For Model Stability: Experience tackling model stability, consistency, and edge-case handling in real-world deployments. Fleet Tooling: Prior work building internal tooling for fleet operations, hardware deployments, or large-scale field systems. Unity & VR: Familiarity with Unity, C#, and VR development. Web Frontend: Familiarity with web frontend technologies. At Dyna Robotics , we build technology for the real world, which requires a team as diverse as the environments our robots inhabit. We are an equal opportunity employer committed to technical rigor and mutual respect. Don’t let a checklist stop you. Data shows that underrepresented groups often only apply if they meet 100% of the criteria. We value problem-solving and grit over keyword matching. If you’re passionate about robotics, no matter your discipline, we want to hear from you, even if you don't check every box.