Software Engineer - Perception and Controls

San Francisco

About Stable:

Stable is an early-stage, venture-backed company building the next generation of charging infrastructure for electric vehicle fleets. Urban charging infrastructure is a critical and underserved area necessary to make electric and autonomous vehicles a reality -- we’re working to fix that. Our founding team is a diverse group of former MIT scientists, Googlers and charging experts with backgrounds in robotics, optimization, and machine learning.

Our investors include Qasar Younis (former COO at Y Combinator), Kent Goldman (Upside VC), Habib Hadad/Calvin Chin (MIT's E14 fund), Reilly Brennan (, Scott Belsky (Founder of Behance), Sunil Paul (Founder of Sidecar), and more.

We are looking for a critical team member to help us build the next generation of electric vehicle charging infrastructure. You will help us build the perception and control subsystems that power our robotic charger. Our robotic charger is a multi-degree of freedom robotic arm that detects and plugs into the charging port of a wide range of electric vehicles. You will be responsible for the core of the software that runs and manages these chargers. Your role will be that of a software engineer, but will have broad responsibilities and you will be expected to tackle large and varied problems to help us scale our business.

You are

  • Kind: Kindness is one of our core values, we value team members who are thoughtful and empathetic
  • Motivated by a challenge: you like taking on hard problems and figuring out creative solutions; you’re not afraid of something just because you don’t know how to do it yet.Creative: solving hard problems requires a healthy dose of creativity, you like to think about new ways to solve things and like to find innovative new solutions. 
  • Naturally curious: You’re naturally curious and like digging into new problems or learning about new things
  • Growth mindset: you thrive on challenge and see failure as a springboard for growth and for stretching our existing businesses
  • Strategic and Analytical: able to analyze, learn, and understand situations quickly and focus on the activities that matter the most
  • Fast to learn and improve: as we’re still early in our company’s evolution t, we work in a hypothesis-driven manner with rapid iteration to figure out what works without fear of failing frequently
  • A strong communicator and influencer: you enjoy working across a diverse team of colleagues and have the ability to get others excited about your initiatives
  • Ready for a startup: you’re excited about working in fast paced, early stage startup environment

Your experience

  • Bachelor's or master's degree in Computer Science or a related field, or have equivalent experience in software engineering roles
  • 2+ years of experience designing, building, and deploying software in a production environment
  • Have a strong understanding of computer vision and machine learning, including experience with camera calibration, object detection, support vector machines and convolutional neural networks.
  • Have a strong foundation in 3D geometry, coordinate systems and linear algebra.
  • Have experience writing software that controls hardware systems under safety-critical conditions, such as robotic grasping/manipulation, path planning for self driving cars, drones or industrial automation.

In this role you will

  • Develop our computer vision algorithms to translate what our robot’s sensors see into actions.
  • Develop motion planning and decision making systems to navigate around obstacles and allow our robots to interact with the world.
  • Design algorithms to grasp and manipulate objects using our robotic arms.
  • Refine our perception and controls software to improve robot reliability and ensure that our robots can safely recover from failure states.
  • Develop tools to calibrate vision-guided robots so our computer vision algorithms work seamlessly across various current and future robot architectures.
  • Build out robust testing infrastructure to ensure that our charging robots can reliably plug in cars in a wide array of environmental conditions.

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