Senior AI/ML Engineer for Time-Series Underwater Acoustics

Optics11; Amsterdam; On-site; EUR 90,000 - 130,000; Full time

Benefits offered by this job

Competitive salary

Cross-functional team

International organization

Personal development opportunities

Lunches

Job summary

Optics11 is seeking a Senior AI/ML Engineer to develop and deploy ML for underwater acoustic sensing using fiber-optic platforms. You will work with acoustics, signal processing, software and embedded teams to deliver robust ML components for real-time operation.

The role emphasizes applied mathematics, statistics and physics-informed ML, with opportunities to push innovation in time-series analysis and sensor fusion for offshore environments.

Qualifications

• MSc in Machine Learning, Signal Processing, Applied Mathematics, Computer Science, Physics, or related field.
• Strong foundation in linear algebra, probability and statistics, and signal processing.
• Experience applying AI/ML to time-series or sensor data; proficiency with CNNs, RNNs (LSTMs) or Transformers.

Responsibilities

• Develop and implement machine learning solutions for underwater acoustic sensing use cases.
• Select modelling approaches based on data availability and system constraints.
• Design, train, evaluate and benchmark AI/ML models with deployment readiness.
• Validate models across laboratory experiments and offshore field datasets.
• Analyze large-scale datasets and contribute to scalable data workflows.
• Collaborate with acoustics, signal processing, software and embedded teams.
• Translate AI/ML results into clear technical insights for system decisions.

Skills

Time-series ML

Applied mathematics

Statistics

Signal processing

Python

PyTorch

TensorFlow

JAX

Education

MSc in ML / Signal Processing / Math / CS / Physics

Tools

PyTorch

TensorFlow

JAX

Job description

Optics11 is seeking a Senior AI/ML Engineer to develop and deploy ML for underwater acoustic sensing using fiber-optic platforms. You will work with acoustics, signal processing, software and embedded teams to deliver robust ML components for real-time operation.

The role emphasizes applied mathematics, statistics and physics-informed ML, with opportunities to push innovation in time-series analysis and sensor fusion for offshore environments.