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Machine Learning Engineer · Netherlands

Senior AI/ML Engineer

optics11·Amsterdam, Noord-Holland, Netherlands

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We are looking for an experienced AI/ML Engineer to develop and deploy machine learning solutions for real-world underwater acoustic sensing systems.

Optics11 is a deep-tech company developing cutting-edge fiber-optic sensing technologies for challenging environments, including underwater acoustics, offshore energy, and defense applications. Our systems enable high-performance sensing and monitoring through advanced photonics, signal processing, and data-driven intelligence.

We are expanding our R&D team with a Senior AI/ML Engineer who combines strong mathematical foundations with applied machine learning expertise to enhance the next generation of intelligent acoustic sensing solutions.

Role Overview:

As a Senior AI/ML Engineer, you will apply machine learning to real-world underwater acoustic sensing challenges using Optics11’s fiber-optic technology platforms. You will work closely with acoustics engineers, signal-processing specialists, and embedded/software teams to develop robust ML components that integrate seamlessly into operational systems.

This role requires a strong foundation in signal processing, applied mathematics, and statistics, and the ability to combine physics-based acoustic algorithms with data-driven ML methods.

Responsibilities:

  • Develop and implement machine learning solutions for underwater acoustic sensing use cases, including detection, classification, localization and anomaly monitoring within fiber-optic sensing systems.
  • Select and adapt modelling approaches based on data availability, operational constraints and system requirements.
  • Apply strong foundations in applied mathematics, statistics and signal processing (e.g., beamforming, spectral analysis, detection pipelines) and integrate these with modern data-driven ML techniques.
  • Design, train, evaluate and benchmark AI/ML models, ensuring robustness, generalization and deployment readiness.
  • Validate models rigorously across laboratory experiments and offshore field datasets, with clear performance tracking and reproducible experimentation.
  • Analyze and interpret large-scale experimental and real-world fiber-optic sensing datasets, contributing to scalable workflows for data preparation, labelling and augmentation.
  • Support technical trade-offs between accuracy, interpretability, latency and real-time or embedded constraints.
  • Collaborate closely with acoustics engineers, signal processing specialists, software and embedded teams to integrate ML components into operational acoustic sensing pipelines.
  • Translate complex AI/ML results into clear technical insights that inform system-level engineering decisions.
  • Contribute to strong engineering practices, including version-controlled experiments, documentation, traceability, validation standards and continuous improvement of ML components.
  • Stay informed about advances in AI/ML for time-series analysis, sensor fusion and signal-informed learning, and prototype promising approaches that complement the broader technology stack.

What's in it for you?

  • Competitive salary .
  • Innovative high-tech, international organization .
  • The opportunity to work in a cross-functional and interdisciplinary environment .
  • A lot to learn and to develop, we stimulate personal development .
  • Lunches.
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