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Senior Machine Learning Engineer

Technologie
DeepRec.ai
Berlin, DeutschlandVor 3 WochenBis 31.5.2026
VollzeitVor Ort

Stellenbeschreibung

Senior Applied AI / ML Systems Engineer

We’re working with an early-stage, mission-driven start-up building a voice-based clinical AI product in a safety-critical domain. They are now making their first dedicated AI/ML hire with the opportunity to shape both the product and the AI foundations from the ground up.

The Role

As a Senior Applied AI / ML Systems Engineer, you will own the LLM application layer and production inference infrastructure. This is a hands-on, high-impact position reporting directly to the CTO.

You’ll be responsible for:

  • Designing and building LLM application & orchestration systems for complex, multi-turn interactions
  • Developing robust model serving & inference infrastructure with strict latency and reliability requirements
  • Driving the AI stack toward clinical-trial readiness
  • Owning evaluation, quality measurement, and real-world performance (not just prototyping)
  • Shipping production ML systems in a safety-critical environment

Must-Have Experience

  • Strong deep learning fundamentals with hands-on training & evaluation experience
  • Proven expertise in LLM application engineering (prompting, context management, orchestration, failure modes)
  • Experience running models in production under real constraints (latency, cost, reliability, monitoring)
  • Demonstrated ability to ship ML/LLM features end-to-end
  • Strong Python and modern ML tooling
  • High autonomy with start-up-level ownership and execution speed

Strong Plus

  • Neurosymbolic or hybrid AI approaches
  • Voice / audio ML experience
  • Background in healthcare, clinical, or other safety-critical domains
  • GCP infrastructure experience
  • German language skills

What They’re Looking For

  • Engineers who understand trade-offs in real systems, including false positives vs. false negatives
  • People who can measure, evaluate, and improve model quality in production
  • Builders comfortable navigating ambiguity and ownership from zero to one

Details

  • Berlin-based (on-site preferred, hybrid possible)
  • Reports directly to the CTO
  • Small, senior team with close collaboration across engineering and clinical stakeholders
  • Competitive startup salary meaningful early-stage equity
Keywords
OrchestrationOCamlPythonDeep learning

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