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← Orcrist Technologies

ML Engineer

Orcrist Technologies
Location
Remote
Posted
2 months ago
Department
Engineering
What they actually want (must-haves)
  • 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
Nice to have
  • 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 the job really is

As an ML Engineer at Orcrist, you will focus on building and productionizing AI capabilities across various domains such as text, vision, and audio. Your role involves evaluating and optimizing open-source models for real-world applications, collaborating with cross-functional teams to transition prototypes into production-ready systems, and contributing to the ML infrastructure and MLOps processes.

Benefits
  • Remote-first, Germany-wide work flexibility
  • Flexible working hours
  • Personal home-office equipment budget
  • 30 days of vacation
  • Investment in personal and professional development
  • Performance bonuses tied to objectives and key results
Things to weigh
  • No salary listed
  • Focus on productionizing existing models rather than training from scratch
  • Role requires collaboration with multiple teams, which may involve varying priorities
Job score2.8/5
Benefits4/5
Freshness1/5
Career value4/5
Role clarity5/5
Pay transparency0/5

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