1X
Software Engineer - NEO Reliability
About this role
1X is hiring a Software Engineer to own reliability and testing across their NEO humanoid robot's entire software stack—from embedded firmware to cloud services. You'll build integrated testing infrastructure, establish SLOs, triage issues across hardware and software boundaries, and scale reliability practices as the company ships robots to thousands of homes.
What you'll do
- Design and build end-to-end testing infrastructure spanning web, cloud, mobile, on-robot services, and embedded systems
- Own hardware-in-the-loop and simulation-based testing that validates robot movement and behavior
- Establish SLOs, error budgets, and observability standards across the full software stack
- Triage reliability incidents, identify root causes across hardware/software boundaries, and route to appropriate teams
- Drive reliability best practices and testing standards across engineering teams and external customers
- Develop metrics and telemetry pipelines to measure robot health, actions, and system performance at fleet scale
What they're looking for
- Full-stack software engineering with deep expertise in at least one layer (cloud/backend, systems, or embedded)
- Test infrastructure and reliability engineering (SRE practices, SLOs, error budgets)
- Python and at least one systems language (C++, Rust, Go, etc.)
- DevOps, Linux, CI/CD, and infrastructure as code
- Distributed systems, APIs, monitoring, and incident management
- Statistical and probabilistic reasoning
- Hardware-in-the-loop and simulation-based testing
- IoT, robotics, or real-time systems constraints and telemetry
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1X
1X builds humanoid robots for home use, with its NEO robot requiring sophisticated hardware, firmware, and cloud systems. The company is hiring across compliance testing, audio systems, embedded firmware, cloud platform development, and supplier engineering to bring its robots to production and scale.
View all jobs at 1XLikely interview questions
- Walk us through a time you built testing or reliability infrastructure from scratch and scaled it—what were the key decisions?
- How would you approach testing a system where hardware and software failures are hard to distinguish? Give a concrete example.