Software Engineer

🏢 Watney · 📍 San Francisco · 💼 onsite · ⏰ FullTime
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Position Summary & Responsibilities

Our Mission

Expand human ambition in the physical world.

Critical infrastructure is constrained by labor shortages, hazardous working conditions, and operational complexity. Watney builds and deploys autonomous robotic systems that increase the speed and capacity of buildout, starting with data centers.

About the Role

At Watney, full stack engineers own our software ecosystem end-to-end, meaning you will regularly cross the boundary between high-throughput backend infrastructure, enterprise customer platforms, and highly interactive web frontend interfaces. As we rapidly scale production deployments and robotics capabilities, you will work on the design and development of our off-robot systems.

 

What You’ll Do

  • Core Platforms: Drive end-to-end development for video-heavy annotation platforms, VR teleoperation interfaces, and secure customer portals.

  • Off-Robot Systems: Build cloud infrastructure, load balancing, and high-throughput pipelines to ingest and process petabyte-scale telemetry streams in real time.

     

You May Be a Good Fit If You:

  • Have 2+ years of full-stack experience contributing to scalable cloud infrastructure, media/video streaming pipelines, or complex rendering systems.

  • Experience with or interest in Rust, or have strong C++/functional programming fundamentals.

  • Have experience operating software at the intersection of physical hardware, complex simulations, or autonomous vehicles.

 

We’re committed to building a diverse, inclusive team. At Watney Robotics, we welcome people of all backgrounds and identities, and we make hiring decisions based on skills, experience, and potential. If you’re passionate about robotics but don’t meet every

🎯 Candidate Preparation Guide For Watney Applicants

Key Role Competencies & Evaluation Highlights

Key Role Focus:

Evaluates data-driven analytical rigor, autonomy, and the ability to extract actionable insights from complex datasets.

📋 Preparation Priorities (Key Areas to Clarify):
  • 1. Getting lost in endless data exploration without driving toward a business recommendation
  • 2. Weak foundational understanding of core statistical concepts
  • 3. Inability to defend methodological choices under constructive pushback
✨ Recommended Role Alignment Hook:

I turn messy, high-volume data into clear operational levers that directly drive top-line and product decisions.

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