Bluetooth diagnostic device and mobile app for DIY car maintenance
OBDeleven makes a Bluetooth diagnostic tool paired with a smartphone app that lets car owners run maintenance checks themselves. The stack—Python, PyTorch, and a full mobile platform (Swift/iOS, Kotlin/Android)—reveals a company building real machine-learning inference on device: the "training predictive models that detect car faults" project sits alongside "LLM-powered business data summarization," suggesting OBDeleven is embedding AI into both the core product and internal operations. Hiring is engineering-led (9 open roles, Head of Engineering as a posted position) and accelerating, with scaling pain points explicitly cited.
Notable leadership hires: Creative Team Lead, Head of Engineering, Engineering Head
OBDeleven is a Lithuania-based automotive diagnostics company that builds a Bluetooth-enabled hardware device and companion mobile application for car owners and mechanics. The product performs real-time fault detection and customization functions, powered by predictive ML models. The engineering organization is actively scaling, supported by growth in marketing and product. OBDeleven operates in a single hiring market (Lithuania) and maintains active projects spanning mobile app feature development, e-commerce platform improvements, and brand expansion.
Core stack: Python, PyTorch, Docker, Node.js/Nest.js, TypeScript, MySQL, MongoDB. Mobile: Swift/SwiftUI (iOS), Kotlin/Kotlin Multiplatform (Android). Distribution via YouTube, Instagram, TikTok.
Core projects: predictive fault-detection models, high-impact mobile features, mobile ecosystem integration, e-commerce platform improvements, LLM-powered business data tools, and process automation for internal workflows.
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