Senior Machine Learning Engineer

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