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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineer, Data Infra - **Company:** Dyna Robotics - **Location:** Redwood City, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Airflow, Amazon Web Services, Batch Processing, Data Visualization, Software Debugging, Distributed Data Store, Python (Programming Language), PostgreSQL, Machine Learning, NoSQL, NumPy, Redis, TypeScript, Cloud Platform System, ReactJS, Grafana, Backend, Pandas, Kubernetes, Machine Learning Operations, Lidar - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/software-engineer-data-infra-dyna-robotics-8139963 ## About the Role * The Experience: 5+ years of professional software experience, ideally with a focus on data-intensive or "human-in-the-loop" platforms. * Technical Stack: Proficiency in Python (NumPy, Pandas) and a solid understanding of modern backend architectures. Experience with React/TypeScript is a major plus for building internal observability tools. * Mathematical Core: Strong skills in algorithms and geometric calculations (e.g., coordinate transformations, 3D spatial reasoning). * Data Mastery: Hands-on experience with relational and NoSQL databases (PostgreSQL, Redis) and cloud-native infrastructure (GCP/AWS). * Problem-Solving: The ability to debug real-world data issues - from sensor drift to pipeline bottlenecks - independently. Bonus Points For: * Experience with multimodal data (video, LiDAR, time-series) in robotics or autonomous systems. * Familiarity with Airflow, Kubeflow, or similar distributed batch processing systems. * Experience with experiment tracking frameworks like Weights & Biases or MLFlow. * Experience as an early hire in a fast-paced startup environment. ## Description As a Software Engineer, Data Infra you are the architect of the "Laboratory" where Dyna's robotic intelligence is refined. You won't just move data; you will build the interactive systems that bridge the gap between raw multimodal sensor streams and production-ready ML models., * Interactive Data Systems: Architect the engines and interfaces that unify raw robot logs, video, and 3D sensor data. You will enable seamless "human-in-the-loop" workflows, from episode annotation to analyzing manual interventions. * Signal Extraction & Geometry: Design and implement algorithms to extract structured signals (trajectories, events, 3D poses) from raw captures. Strong mathematical intuition is required to turn pixels and point clouds into ground-truth insights. * Evaluation & Benchmarking: Build high-performance tools to compare model-driven motion against human-captured data, helping the team quantify model progress across diverse tasks. * Scalable ML Pipelines: Build and operate distributed data pipelines (using Python, GCP/AWS, and Kubernetes) for the ingestion, transformation, and validation of terabytes of multimodal data. * Observability & Debugging: Develop visualization tools that make complex model behaviors and sensor data easy to interpret, reducing the time from "data collected" to "model trained." * Startup Fluidity: Collaborate across ML, Robotics, and Product teams. As an early member of the data team, you will help define the roadmap where no blueprint yet exists. ## Related Videos - [How to develop an autonomous car end-to-end: Robotic Drive and the mobility revolution](https://www.wearedevelopers.com/videos/22-how-to-develop-an-autonomous-car-end-to-end-robotic-drive-and-the-mobility-revolution) - [Robots are coming into the wild! Full-Stack Robotics Engineers, be ready!](https://www.wearedevelopers.com/videos/479-robots-are-coming-into-the-wild-full-stack-robotics-engineers-be-ready) - [Reducing LLM Calls with Vector Search Patterns - Raphael De Lio (Redis)](https://www.wearedevelopers.com/videos/1714-reducing-llm-calls-with-vector-search-patterns-raphael-de-lio-redis) - [Vectorize all the things! 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