EM Data Scientist – ML for Electromagnetic Sensing

Metrea; Greater London; Hybrid; GBP 70,000 - 110,000; Full time

Benefits offered by this job

Private Medical Insurance

Subsided gym membership / plans

Electric Car scheme

Cycle to work scheme

Free lunch on office days

Enhanced Parental Leave

30 days annual PTO plus bank holidays

Bonus Scheme

Personal development opportunities

Job summary

Metrea in the United Kingdom is seeking a Machine Learning Scientist to apply ML, data science and advanced analytical methods to electromagnetic challenges within DESLAB and the automated Solution Engine. You will design, test, and deploy ML-enabled capabilities that go beyond traditional signal processing approaches.

You will explore transformers, self-supervised learning, probabilistic modelling and simulation-driven learning for electromagnetic sensing and exploitation, turning complex

Qualifications

• Post-doctoral degree or Master’s degree in a quantitative STEM field.
• Familiarity with CNNs, Transformers, autoencoders, or self-supervised learning.
• Excellent communication skills to explain complex ML/RF concepts.

Responsibilities

• Translate operational requirements into technical solutions with cross-functional teams.
• Apply ML/DS techniques to electromagnetic problems like spectrum classification and emitter detection.
• Develop experiments to evaluate new algorithms and deploy proofs-of-concept into operations.
• Mentor junior team members and contribute to a collaborative, rigorous environment.

Skills

Python

ML/DS

RF/EM concepts

Collaboration

Communication

Education

Post-doctoral or Master’s in STEM

Tools

Python scientific stack

Job description

Metrea in the United Kingdom is seeking a Machine Learning Scientist to apply ML, data science and advanced analytical methods to electromagnetic challenges within DESLAB and the automated Solution Engine. You will design, test, and deploy ML-enabled capabilities that go beyond traditional signal processing approaches.

You will explore transformers, self-supervised learning, probabilistic modelling and simulation-driven learning for electromagnetic sensing and exploitation, turning complex