About Us:We’re a VC-backed stealth-mode company building behavioural AI solutions for the retail industry. Our platform is designed from the ground up — no legacy, no patchwork systems — just a clean slate and a clear vision. Our mission is to bring the intelligence of modern machine learning directly to the in-store experience, powering real-time, context-aware interactions in physical retail environments through beautifully engineered mobile experiences.Role:We're looking for an experienced Android Engineer to help with the development of a cutting-edge consumer facing app designed to change the physical in-store shopping experience. You’ll collaborate closely with our team of ML & backend engineers and product to deliver a mobile experience that feels fast, personalised, and deeply responsive to user context. Responsibilities:Architect and drive the development of complex Android features, including robust real-time communication and bi-directional data flows.Design offline-first architectures, implementing sophisticated prefetching, caching, and background sync engines.Take ownership of app performance, profiling and optimising for low latency, memory efficiency, and battery life in a resource-intensive environment.Integrate complex ML features into the UI/UX, bridging the gap between the Edge AI team’s models and the user interface.Define and evolve the mobile codebase using modern architectural patterns (MVI/MVVM, Clean Architecture) to ensure scalability.Mentor and collaborate, working closely with product and design to turn complex technical capabilities into polished user interactions.Essential Qualifications:Experience with real-time protocols and data-heavy applications (e.g. WebSockets, gRPC, MQTT, SSE).Expert-level understanding of Android internals: concurrency, memory management, and the full lifecycle constraints.Proven track record of building resilient, offline-capable systems (familiarity with sync queues, local databases, and reactive flows).Ability to architect for complexity, handling asynchronous data streams and complex state management cleanly.Comfort working in fast-paced, product-driven environments where you are expected to make high-level technical decisions.Curiosity about behavioural data and context-aware design.What Sets You Apart:Exposure to integrating machine learning features (e.g. ML Kit, or custom TFLite models) into a production app.Experience with hardware integration (Bluetooth, Sensor APIs, or USB-C peripherals).Background in early-stage product design or MVP development.
Updated: 10 February 2026
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