3D Computer Vision Researcher (World Modeling for 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 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). Who you are 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. Where you are San Francisco, CA Technical skills Broad technical foundation in software engineering and deep learning (through self-study, practical experience, or PhD) 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/WebDataset) Backend: experience designing and building scalable and high availability server-side systems (Python, NodeJS, or Golang) Cloud: familiarity with DevOps and infrastructure (i.e. Docker, Kubernetes, GPU scheduling) on cloud (i.e. GCP, AWS) Monitoring: experience with logging systems and monitoring tools such as DataDog, Sentry, and/or CloudWatch 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 GitHub, GitLab, etc. Domain-specific: spatial data and analytics, geographic information systems, spatial databases (PostGIS) #J-18808-Ljbffr Jaide Health