Orcrist Technologies - (Senior) Machine Learning Engineer

• Evaluate, compare and integrate open-source models for concrete product and customer use cases. • Build and improve LLM-based applications. • Extend and improve AI and ML models using inference optimization, evaluation, and fine-tuning where appropriate. • Work with NLP, translation, speech-to-text / ASR, image and document understanding, and related applied AI models. • Design evaluation frameworks covering model quality, latency, reliability, and cost. • Take models from experimentation into production, including packaging, deployment, monitoring, and iteration. • Optimize inference performance and operational cost. • Collaborate with Research and Product teams to turn prototypes and experiments into scalable product capabilities. • Contribute to modern ML infrastructure and MLOps while remaining hands-on with models and model behaviour. • 4+ years of experience in Machine Learning Engineering, Applied AI, or a similar hands-on ML role. • Strong Python skills and practical experience with modern ML frameworks and libraries such as PyTorch, Transformers, and Hugging Face. • Experience working with LLMs, NLP models, speech models, or other modern generative AI systems. • Hands-on experience evaluating and experimenting with existing models rather than only building ML infrastructure. • Experience with inference engines like vLLM or SGLang, and platforms like NVIDIA Triton or Ollama. • Familiarity with fine-tuning, prompting, model evaluation, inference, and deployment. • Working understanding of AI model encoding and quantization formats, and the tradeoffs thereof. • Strong engineering mindset and ability to turn experiments into reliable, reproducible systems. • Eligible to work in Germany; export-control screening required for certain programs. • Nice-to-haves • Hands-on experience with model serving and production deployment, using technologies such as Kubernetes, KServe, NVIDIA Triton, and/or Ray Serve. • Knowledge of inference optimization techniques, including batching, quantization, ONNX, or TensorRT. • German language skills (B1+) and/or familiarity with defense or public safety datasets. • Exposure to geospatial AI, satellite imagery, or remote sensing. • Experience working in constrained or regulated environments with infrastructure, security, or deployment requirements.