Machine Learning Engineer (m/f/d) 
Company
Orcrist is building a next generation data intelligence platform using cutting-edge
technologies. We’re handling petabyte-scale data with sub-second queries. Our product
is a Kubernetes-based platform delivered as B2B SaaS or as a self-hosted on-prem
solution, including air-gapped deployments. We enable customers across defense, law
enforcement, and enterprise to turn mission-critical data into actionable intelligence by
fusing data processing, ML, and intuitive UX.
Role
We are looking for a hands-on ML Engineer to build and productionize modern AI
capabilities across text, vision, audio, and other applied ML use cases. You will work
directly with state-of-the-art and open-source models — testing, evaluating, optimizing,
and fine-tuning them for real product use cases. This is not a role focused on training
foundation models from scratch or building data pipelines only. You will work closely
with Research, Product, and Data Engineering teams to take promising models and
ideas from experimentation to reliable, production-ready systems.
What you’ll do
? 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.
About you
? 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.
What we offer
? The opportunity to work hands-on with modern AI and open-source models.
? A modern ML stack and real-world product use cases.
? Close collaboration between Research, Product, and Engineering.
? Remote-first in Germany with regular Berlin meetups, 30 days vacation,
equipment & learning budget.
How to apply
Send your CV, links to relevant repos/papers, and a short summary of production ML
accomplishments to careers@orcrist.org. Include availability and compensation
expectations.