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.
Required Qualifications
-
MSc in Machine Learning, Signal Processing, Applied Mathematics, Computer Science, Physics, or a related field.
-
Strong foundation in linear algebra, probability, statistics, and signal processing.
-
Proven experience applying AI/ML methods to time-series or sensor data, including techniques such as: Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs) (e.g., LSTMs), Transformer-based architectures for time-series learning.
-
Supervised and unsupervised learning approaches for detection and classification.
-
Hands-on experience with model training, evaluation, and validation in applied settings.
-
Proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow, JAX).
-
Ability to work in an applied R&D environment with experimental and field data, balancing model performance with real-world constraints.
Nice to Have
-
Experience with underwater acoustics, sonar, or beamforming-related applications.
-
Knowledge of embedded or real-time deployment constraints.
-
Experience with sensor fusion, self-supervised learning, or physics-informed ML.
-
Familiarity with offshore, defense, or industrial monitoring domains.
-
Familiarity with structured ML development processes such as CRISP-ML(Q) or similar lifecycle and quality frameworks.
You'll be working with clients in the defense and security sectors, obtaining a Certificate of No Objection issued by the AIVD (Dutch General Intelligence and Security Service) is mandatory. This means you will need to undergo a security screening. For more information, please refer to details on security screening.
More information
So now you know we're doing awesome projects and if you see you fit the profile we would like to get to know you. Apply or, in case of questions, get in touch with our recruiter Dóra Öveges ( [email protected]).
