Atomic Machines

Staff Systems Engineer - Software Systems

Atomic Machines
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2 months ago
Santa Clara, CA, USAStaff+
H1B Sponsor

Base Salary

$170k - $215k/yr

Responsibilities

  • Architect software systems spanning embedded systems, controls, cloud services, robotics, and manufacturing applications.
  • Define software interfaces between platform services, robotics, and hardware.
  • Implement critical infrastructure, APIs, communication protocols, and distributed services.
  • Build automated testing, simulation, integration, and validation tools.
  • Design and execute software validation, verification, and system integration testing.
  • Drive performance, latency, synchronization, and reliability improvements.
  • Lead debugging across hardware and software boundaries and drive FMEA, trade studies, and root-cause investigations.

Requirements

  • Extensive Python development experience and strong software architecture experience are required.
  • Seven or more years of experience building complex software systems is required.
  • Experience with distributed systems, networking, gRPC, APIs, messaging systems, and IPC is required.
  • Experience integrating software with robotics and industrial hardware is required.
  • Experience developing automated testing infrastructure, simulation, and software verification is required.
  • Familiarity with embedded systems and real-time software is required.
  • Experience with C++, Rust, or Go is preferred.
  • A BS or MS in Computer Engineering, Software Engineering, Computer Science, or equivalent is required.
  • A first-principles systems mindset is expected.

Benefits

  • Equity and benefits are included in the compensation package.
  • The role may be based in Emeryville or Santa Clara, California.

Tech Stack

Categories

Atomic Machines

About Atomic Machines

51-200 employees

Atomic Machines is on Earth to radically advance humanity's command of matter. Our MC-1 manufacturing technology embodies this mission at the micro-scale, both blowing open the design space ("MEMS 2.0") and doing so in a way that enables extremely rapid iteration and scaling to high-volume manufacturing ("thought to thing time"). Our first device product establishes a new price-performance class highly relevant to the AI data center space.