Senior Machine Learning Engineer

develop; München; Vor Ort; EUR 110.000 - 150.000; Vollzeit

Zusammenfassung

develop, based in Munich, seeks an experienced Senior ML Engineer to build and deploy next-generation ML models for edge processing of acoustic data in real-time defence and security applications.

Ideal candidates have hands-on Python expertise with PyTorch or TensorFlow, edge AI experience, and a strong background in signal processing and real-time systems. Fluent German and English are required, with full on-site presence in Munich.

Qualifikationen

• Several years of hands-on experience building, training, and deploying production-grade machine learning models in real-world environments.
• Strong Python expertise and deep learning frameworks (PyTorch/TensorFlow).
• Experience with edge AI, model optimization, and signal processing.
• Domain mindset in applied physics, defence technology, IoT, or real-time sensor intelligence.
• Fluent German and English communication skills, with full on-site availability in Munich (5 days per week).

Aufgaben

• Design, train, and optimize advanced machine learning models and foundation architectures capable of processing non-speech audio at the edge.
• Deploy and scale ML pipelines on ultra-low-power sonic devices with high reliability and low latency for real-time event detection, classification, and localization.
• Collaborate with physics, mechanical engineering, and product teams to translate complex environments into robust, production-grade intelligence systems.

Jobbeschreibung

• Location: On-site (5 days per week) in Munich, Germany
• Language: B2+ German and English required

Role Overview

My client is looking for an experienced Senior ML Engineer to join. They are a start-up AI and Defence security intelligence company in Munich. The role focuses on developing next-generation machine learning systems, foundation models, and edge intelligence that turn complex acoustic data into real-time operational awareness for defence and homeland security missions.

Key Responsibilities

• Model Development & Training: Design, train, and optimize advanced machine learning models and foundation architectures capable of processing non-speech audio at the edge.
• Edge & System Integration: Deploy and scale ML pipelines on ultra-low-power sonic devices, ensuring high reliability, low latency, and real-time event detection, classification, and localization.
• Cross-Functional Collaboration: Work closely with physics, mechanical engineering, and product teams to translate complex physical environments into robust, production-grade intelligence systems.

Profile & Requirements

• Experience: Several years of hands-on experience building, training, and deploying production-grade machine learning models in real-world environments.
• Technical Stack: Strong Python expertise, deep learning frameworks (PyTorch/TensorFlow), and experience with edge AI, model optimization, and signal processing.
• Domain Mindset: Strong interest or background in applied physics, defence technology, IoT, or real-time sensor intelligence.
• Prerequisites: Fluent German and English communication skills, and full on-site availability in Munich (5 days per week) with valid work authorization in Germany.