About Kinetic Kinetic Automation is building a network of automated repair centers for modern vehicles. The auto industry is transitioning from mechanically complex vehicles to mechanically simple ones with complex software and technology. Backed by Menlo.
About the role
You will be a part of a small, production-minded ML team based in Orange County/Oakland. You’ll collaborate with other engineers and researchers to develop, evaluate, and help deploy vision models for tasks like semantic/instance segmentation and object/damage detection across 2D and 3D data.
What they're looking for
- Curiosity & Strict Attention to Detail: You are obsessed with corner cases. You have a sharp eye for data anomalies, run rigorous ablations, keep meticulous experiment logs, and can clearly communicate trade-offs
- Working knowledge of transformer and LLM building blocks applied to vision, including self-attention, positional encodings, tokenization, and mapping these ideas to vision models (e.g., ViT, DETR, Mask2Former)
- Practical exposure to 3D/depth data, including familiarity with point clouds, camera geometry (intrinsics/extrinsics), basic calibration, and multi-view geometry
- Proficiency in Python and the relevant tech stack: PyTorch, torchvision, Detectron2 or MMDetection/Segmentation, and Hugging Face Transformers
- Experience with Python services (FastAPI/Flask), Docker, and AWS services (S3, Batch/EC2, ECR) is preferred
- Strong communication skills with the ability to write tidy PRs, experiment logs, and short design notes to ensure reproducibility
More about this role
You will be a part of a small, production-minded ML team based in Orange County/Oakland. You’ll collaborate with other engineers and researchers to develop, evaluate, and help deploy vision models for tasks like semantic/instance segmentation and object/damage detection across 2D and 3D data.
- Deep ML / CV Fundamentals: You need hands-on experience training and evaluating deep models for segmentation and detection (PyTorch). You must understand how Transformer/LLM building blocks map to vision (ViT/DETR/Mask2Former) and have practical exposure to 2D/3D data, point clouds, and camera geometry
- Curiosity & Strict Attention to Detail: You are obsessed with corner cases. You have a sharp eye for data anomalies, run rigorous ablations, keep meticulous experiment logs, and can clearly communicate trade-offs
- AI-Empowered, Not AI-Dependent: We strongly encourage leveraging AI tools (Copilot, ChatGPT, Claude) to maximize your efficiency. However, you must 100% understand the underlying details of the code you ship. We are looking for strong independent thinkers and debuggers, not someone who simply passes along AI outputs without deep comprehension
- Working knowledge of transformer...
Browse similar: AI jobs · AI startup jobs · Startup jobs