Software Development Engineer – Robotics & AI Job Sunnyvale area,California USA,Software Development

Work Authorization: W2 only. We are unable to work with candidates requiring visa sponsorship or third-party/C2C arrangements.

Summary

We are seeking a Software Development Engineer to build tools and infrastructure that improve the reliability, maintainability, and testability of complex robotic systems. This role combines robotics, automation, developer infrastructure, and machine learning, with opportunities to work closely with hardware, firmware, simulation, and ML engineering teams.

Key Responsibilities

Develop tools for diagnosing, maintaining, and upgrading robotic systems.
Build automation for troubleshooting, issue triage, remediation, approvals, and operational workflows.
Develop systems for tracking robots, software, ML models, firmware, configurations, and test assets.
Build automated testing, regression, and verification workflows.
Support software environment reproduction, debugging, and system-level testing.
Improve observability through logging, metrics, dashboards, alerts, and diagnostic tools.
Support ML inference testing and performance evaluation.
Collaborate across engineering teams and contribute to technical documentation and design reviews.

Basic Qualifications

Bachelor’s degree in Computer Science, Computer Engineering, Robotics, or a related field, or equivalent experience.
Strong software development experience with Python and C++.
Experience with Linux, distributed systems, networking, debugging, and automation.
Experience building production-quality software, backend services, developer tools, or system integrations.
Familiarity with APIs, databases, structured data, and workflow/event-driven systems.
Strong problem-solving and communication skills.

Preferred Qualifications

Experience with robotics, autonomous systems, embedded systems, or hardware-in-the-loop.
Experience with CI/CD, test infrastructure, containers, cloud, or infrastructure-as-code.
Knowledge of ML deployment, inference runtimes, GPU acceleration, or performance benchmarking.
Experience with simulation, robot fleet management, configuration management, or experiment tracking.
Experience with AI-assisted knowledge systems, search/retrieval, observability, or production automation.