Ohme manufactures and operates smart charging hardware and software for residential EV owners. The tech stack reveals a hardware-first company: embedded systems (Kotlin, C++, FreeRTOS, ESP32, NB-IoT) paired with cloud backend (AWS, Python, SageMaker, TensorFlow), indicating both physical device firmware and ML-driven tariff optimization running in parallel. Active projects around market auctions, AI product integration, and MLops infrastructure suggest Ohme is moving beyond simple time-of-use switching toward dynamic pricing algorithms — a higher-margin play than commodity hardware.
Ohme designs and sells smart home EV chargers that optimize charging time and cost by integrating real-time energy pricing data. The company serves homeowners and workplace charging operators across the UK, France, Australia, and Ireland. Core technology combines embedded firmware (managing charge scheduling on the device itself) with cloud-side machine learning (pricing prediction and tariff matching). Revenue likely splits between hardware sales and recurring software/platform fees. The hiring mix skews senior engineering (6 open roles, 12 senior headcount overall) concentrated in embedded systems and data infrastructure, suggesting scaled manufacturing and data pipeline challenges typical of hardware-software hybrids at 200+ employee scale.
Embedded (Kotlin, C++, FreeRTOS, ESP32, NB-IoT), cloud backend (AWS, Python, SageMaker, TensorFlow, Docker), and networking (MQTT, HTTP/S, LTE). Recently migrating Vue frontend apps to Next.js.
Market auction platform access, B2C/B2B customer experience layers, AI-driven product strategy, MLops infrastructure optimization, and frontend modernization (Vue to Next.js migration).
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