(Senior) Machine Learning Engineer

Orcrist Technologies
Berlin, Germany
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
4 years minimum
Working hours
Regular working hours
Languages
German
Job source

Tech stack

Artificial Intelligence Encodings Information Engineering Information Extraction Python (Programming Language) Machine Learning Performance Tuning Inference Optimization Tensorflow Software Deployment Speech Recognition Pytorch
+15 more
Large Language Models Model Validation Generative AI Discretization Kubernetes ONNX (Open Neural Network Exchange) Format HuggingFace SGLang Ray Serve Reasoning Engines Ollama Machine Learning Operations TensorRT Data Pipelines KServe

Job description

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., * 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., * Your setup, your way: Get a personal home-office equipment budget to create a workspace that works for you.
  • 30 days of vacation: Take the time you need to recharge and come back with fresh energy.
  • Keep growing: We invest in your personal and professional development.
  • Get rewarded for impact: Performance bonuses are tied to agreed objectives and key results.
  • A warm welcome: Every new team member gets a welcome goodie bag.
  • Good people, good times: From summer and Christmas parties to regular team gatherings, we make time to celebrate together.
  • A mission that matters: Work on challenges with tangible impact on public safety and national security.

Requirements

  • 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., * 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.

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