Software Engineer, Applications

Join us to shape the next frontier of AI-driven robotics!

Dyna Robotics makes general-purpose robots powered by a proprietary embodied AI foundation model that generalizes and self-improves across varied environments with commercial-grade performance. Dyna's robots have been deployed at customers across multiple industries. Our frontier model has the top generalization and performance in the industry.

The Role

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.

What You Will Do

• 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.

• 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.

• 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 and 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.

• 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

• 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.

• At least 3 years of professional experience as a versatile software engineer, with strong capabilities in both backend systems and broad application-level software.

• Proficient in the Python ecosystem.

• 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).

• Experience with containerization, orchestration (Docker, Kubernetes), and cloud architecture (AWS, GCP, Azure).

• Highly adaptable and comfortable working across a varied tech stack.

• Strong cross-domain communication skills, with the ability to collaborate effectively with Operations, AI researchers, hardware engineers, and platform teams.