Senior Software Engineer, ML Data Platform

Company Overview :

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. Its frontier model has the top generalization and performance in the industry.

Dyna Robotics was founded by repeat founders Lindon Gao and York Yang, who sold Caper AI for $350 million, and former DeepMind research scientist Jason Ma. The company has raised over $140M, backed by top investors, including CRV and First Round.We're positioned to redefine the landscape of robotic automation. Join us to shape the next frontier of AI-driven robotics!

Position Overview

We are seeking a Senior Software Engineer, Data Platform to join our onsite team in Redwood City, California. In this hands-on role, you will design, implement, and maintain systems that process multimodal robot data to extract meaningful insights. This includes developing algorithms for automatic labeling and detecting data quality issues in order to improve our machine learning models. Strong mathematical skills-particularly in algorithms and geometric calculations for extracting signals from video and 3D sensor data-are essential.

You will collaborate closely with machine learning engineers and product leaders, contributing to backend systems, APIs, and machine learning infrastructure as needed. If you thrive in a fast-paced startup environment and are excited to solve challenging engineering problems with cutting-edge technologies, we'd love to hear from you!

Key Responsibilities

• Develop and implement algorithms to process and analyze video and sensor data.
• Utilize ML models and mathematical calculations to extract signals from video and 3D sensor data.
• Build, test, and maintain robust data pipelines and workflows.
• Collaborate with engineers, researchers, and product team members to identify data needs and develop solutions.
• Improve machine learning models by providing high-quality processed data.
• Contribute to other backend systems, APIs, and machine learning infrastructure as needed.
• Leverage cloud computing platforms (AWS or GCP) for scalable processing and optimization.

Qualifications

Preferred Qualifications