3D Computer Vision Researcher; Modeling Autonomous Driving

Our work

We are a well capitalized stealth VC-backed startup building a new type of spatial AI capable of universally solving autonomy. We innovate at the foundational layer of AI by training our own AI models.

Our team is composed of AI pioneers and leaders from Google X, Google Brain, and Space Agencies. Several of us are repeat founders, with deep commercialization insights across multiple enterprise segments. We enjoy long, deep ideations around entirely unexplored AI use cases in autonomy (cars, drones, robots).

• Curious: you have an innate curiosity for all things intellectual, and it’s something you can’t turn off. You obsess over finer details others miss.
• High intensity: you thrive in a high-stakes environment, and are driven by an innate obsession, not by others.
• Fast learner: you gravitate toward learning new things, and often find yourself learning more quickly than everyone around you.
• Driven by discomfort: you enjoy leaving your comfort zone and challenging yourself
• Creative: track record of solving hard problems with solutions worthy of academic papers
• Educator: you take pride in your ability to communicate complex topics clearly and have excellent speaking and writing skills.
• Zero ego: you don’t just take feedback, but truly see it as a gift. You don’t wait until feedback is given, but solicit it with every opportunity.
• Founder mentality: you roll up your sleeves to help solve the most pressing problem on a given day, even if it has nothing to do with this job post.

San Francisco, CA

• Deep learning research: publications at top ML venues, or practical experience training multimodal foundation models
• Trained LLMs, LVMs, or any foundation model
• Product: experience with defining, building, and launching new products
• Programming: deep knowledge of Python
• ML: knows the theory and applied side of deep learning, especially computer vision and foundational model architectures (PyTorch, OpenCV, Tensorflow)
• Robotics: experience here is a plus, but not required.
• Data: experience with distributed data pipelines (Beam/Spark/Web Dataset)
• Backend: experience designing and building scalable and high availability server-side systems (Python, NodeJS, or Golang)
• Cloud: familiarity with Dev Ops and infrastructure (i.e. Docker, Kubernetes, GPU scheduling) on cloud (i.e. GCP, AWS)
• Monitoring: experience with logging systems and monitoring tools such as Data Dog, Sentry, and/or Cloud Watch
• Security: familiarity with enforcing security standards as well as other data regulation compliances (i.e. GDPR, SOC2)
• Version Control: knows the ins and outs of Git and has extensive experience collaborating with teams on systems like Git Hub, Git Lab, etc.
• Domain-specific: spatial data and analytics, geographic information systems, spatial databases (PostGIS)