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Machine Learning Engineer
MARSS GroupMachine Learning Engineer at MARSS improving NiDAR software in areas like video classification, detection, and anomaly detection. Collaborating with a multicultural team in a hands-on maritime safety environment.
Tech Stack
Tools & technologiesKerasPythonPyTorchTensorflow
About the role
Key responsibilities & impact- Help collect and categorize data from public sources as well as from our customer base (when authorized).
- Support training data workflows — we outsource annotation, but data still needs validation and sometimes transformation for the target network.
- Improve test performance and ensure compatibility with new hardware — not only in the NVIDIA ecosystem with the Jetson edge platform, but also on programmable FPGAs and server-grade CPUs (e.g., Intel).
- Test, improve, and tune existing algorithms (neural networks, Bayesian/Markov models, decision trees, reinforcement learning networks, Gaussian models, etc.).
- Port existing solutions (and training data) to different frameworks.
Requirements
What you’ll need- We are technology-agnostic but favor TensorFlow, Keras, and PyTorch. Strong Python skills are important both for data analysis and for integrating with our Python-based backend.
- We require either practical work experience or solid theoretical knowledge (or both).
- Education: bachelor’s degree in a science or engineering discipline preferred; master’s degree or PhD is an advantage.
Benefits
Comp & perks- Prestigious location: Overlooking the Monaco Grand Prix circuit and port.
- Outdoor sports paradise: nearby mountains for skiing, excellent cycling routes, and of course the sea.
- Small team: adopting modern development practices.
- New ideas are encouraged — we try most things but always keep what works for us.
- Diverse team: our local Monaco team is multicultural, combining experienced engineers with top recent graduates.
- Passionate environment: we are passionate and enjoy what we do!
ATS Keywords
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Hard Skills & Tools
Pythonneural networksBayesian modelsMarkov modelsdecision treesreinforcement learningGaussian modelsdata analysisalgorithm tuningdata validation