Orcrist Technologies - Director of Research

• Define and own the company research strategy aligned with product priorities and multi-team technical leverage. • Build and lead a world-class research team of AI researchers, data scientists, and research engineers. • Lead first-principles research in domains such as ASR, translation, information extraction, multimodal reasoning, visual pattern recognition, graph/temporal reasoning, and statistical analysis. • Build the external R&D pipeline: identify opportunities, shape bids, build consortia, author work packages, and act as scientific/technical lead in awarded projects. • Establish research operating discipline: reproducibility standards, benchmark suites, experiment tracking, model/data documentation, and portfolio reviews. • Drive transfer into delivery teams by producing adoption-ready research packages, not just prototypes or papers. • Represent Orcrist externally across customers, partners, universities, RTOs, industry associations, and public funding bodies. • Shape IP and dissemination strategy for research outputs together with leadership and legal stakeholders. • Partner closely with Innovation, Insights, Foundation, Platform, and customer-facing teams. • Coach senior researchers and raise the bar for technical writing, scientific judgment, and cross-functional influence. • 8+ years in applied AI/ML research, data science, or equivalent deep-technical R&D roles. • 3+ years leading research programmes, senior researchers, or cross-functional R&D initiatives. • Deep expertise in machine learning / AI research with strong mathematical and statistical foundations. • Expert Python; strong command of PyTorch and CUDA-backed model development. • Experience with distributed training / research infrastructure (e.g. Ray, Horovod, multi-GPU workflows). • Strong grounding in evaluation design, error analysis, benchmark construction, and reproducible experimentation. • Comfort moving between research and applied systems concerns, including inference constraints and deployment trade-offs. • Experience across one or more of: NLP, speech/audio, translation, CV, multimodal systems, knowledge graphs, temporal reasoning, or applied statistics on structured data. • Track record of original research that produced practical impact: shipped capabilities, patents, influential prototypes, or externally recognised outputs. • Proven experience winning or materially shaping collaborative R&D proposals, grants, tenders, or consortia. • Strong technical writing: research memos, proposals, work packages, and external-facing technical narratives. • Player-coach mentality: high standards, low ego, hands-on when needed. • Eligible to work in Germany. • German language (C1+) and comfort working in German/EU public-sector environments. • Nice-to-haves • Publications, patents, open-source contributions, or recognised external technical profile. • Experience with EU/public R&D programmes such as EDF, Horizon Europe, DIANA, EUDIS, or similar ecosystems. • Experience in defence, law enforcement, geospatial, or intelligence-adjacent domains. • Familiarity with research-to-production ML systems (e.g. Triton, KServe, MLflow). • Existing network across universities, RTOs, primes, SMEs, or European innovation bodies.