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Data Operations & Labeling Specialist (all genders)

Organismo
Stark
País
🇩🇪 Alemania
Lugar
Munich
Puestos
1
Tipo de vínculo
privado

Descripción del puesto

About Us STARK is a new kind of defence technology company revolutionizing the way autonomous systems are deployed across multiple domains. We design, develop and manufacture high-performance unmanned systems that are software-defined, mass-scalable, and cost-effective. This provides our operators with a decisive edge in highly contested environments. We're focused on delivering deployable, high-performance systems — not future promises. In a time of rising threats, STARK is bolstering the technological edge of NATO Allies and their Partners to deter aggression and defend Europe — today. About the team The Data Operations team owns the entire data lifecycle behind STARK's AI stack: collection, acquisition, generation, curation, and management. We run our own data-collection campaigns across Europe, evaluate new sensors and platforms, and build the internal data platform that turns raw recordings into ready-to-use datasets. Everything we produce feeds directly into the perception and autonomy systems deployed on STARK's platforms — a real data advantage is built, not bought. The team is scaling up right now: real scope, direct impact, no legacy. Your mission You are the crucial bridge between our raw field data, our external labeling partners, and our internal Machine Learning teams. Your mission is to ensure our AI models are trained on the highest quality data possible. You will own the day-to-day operations of the data labeling lifecycle: curating raw data, preparing annotation batches, managing vendor communication, and rigorously assessing the quality of incoming labels. If you are highly organized, detail-oriented, and interested in the intersection of data operations and Computer Vision, this is the perfect place to start your career in AI. Responsibilities Own the day-to-day data labeling lifecycle: curate raw field data, create annotation batches, and prepare deliveries for external labeling companies. Serve as the primary point of contact for external data

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