Abstract: Distributed machine learning (DML) may become an important component of IoT device fleets and smart homes in the future. However, it currently presents challenges where reliable (or frequent) internet connectivity is necessary, or trust is not handled. Since DML is generally decentralized and often relies on peer-to-peer networks, we argue that BitTorrent as a time-proven protocol in this space could aid in building a solution. This paper explores the possibilities of employing BitTorrent mechanisms for gossip-based DML. It provides initial evidence supporting the viability of this approach by analysing the behaviour of model training in a simulator representing 30 individual peers with distinct data sets.