sauron.systems-posted 11 days ago
Full-time • Executive
San Francisco, CA

Sauron protects your family and home, bringing the innovations of autonomous robots and self-driving cars to residential security. Our team is led by veteran entrepreneurs and roboticists, alumni of Sonos, Tesla, Apple, and Google. Sauron has raised an $22M seed round led by A and Atomic with participation from other leading venture capital firms and angel investors, including Abstract, 8VC, and Flock Safety CEO Garret Langley. The Role | Vice President Software Engineering We Value Impact: Taking ownership of the core technology and driving it from prototype to mass production. First Principles: Applying sound computer science fundamentals to solve novel problems in hardware, perception, and residential security. Building: Inspiring and developing a team of engineers, fostering a culture of continuous learning and innovation.

  • Architecting, building, and scaling the entire software platform, including firmware for embedded devices, machine learning model deployment pipelines, and our cloud infrastructure.
  • Providing technical leadership and mentorship to the software team, driving best practices in design, development, and testing.
  • Leading the long-term functional engineering team development roadmap to ensure we have the skillsets, capabilities and workflows to enable successful execution of current and future programs.
  • Collaborating with hardware, product, and operations teams to define requirements and deliver a unified, secure, and reliable end-to-end user experience.
  • Recruiting, hiring, and onboarding top-tier engineering talent to grow the organization efficiently and effectively.
  • 10+ years of engineering experience, with 5+ years in a senior leadership role (Director or VP) at a fast-growing, technically complex company.
  • Direct, hands-on experience with the unique challenges of our core pipelines: either Embedded Systems development (e.g., real-time OS, low-latency communication, resource optimization) or Machine Learning implementation (e.g., model quantization, on-device inference, MLOps).
  • Expertise in building systems that require high performance and careful memory management.
  • Proven track record of shipping highly reliable, commercial products that combine hardware and software.
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