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ML Engineer - Applied Machine Learning
Actively Reviewing
RONNACH Technologies
Job Description
Data & Analytics| Mar 23, 2026
About The Position
As an ML Engineer, you will work with real sensor data to design, develop, and validate machine learning models that operate in both real‑time and offline environments.
Responsibilities
What You’ll Do
Junior (0–2 years)
Required
About The Position
As an ML Engineer, you will work with real sensor data to design, develop, and validate machine learning models that operate in both real‑time and offline environments.
Responsibilities
What You’ll Do
- Design and train ML models for prediction, anomaly detection, and signal intelligence.
- Preprocess and analyse time‑series, spectral, and physical signals.
- Build data pipelines for experimentation and deployment.
- Perform controlled experiments and validate models in lab and real settings.
- Collaborate with hardware, firmware, and R&D teams.
- Produce rigorous documentation of methods and results.
Junior (0–2 years)
- Implement ML models and run experiments.
- Prepare and structure sensor datasets.
- Support data collection and prototype testing.
- Document results and contribute to R&D cycles.
- Lead the design of ML pipelines and modelling strategies.
- Apply advanced time‑series, signal‑processing, or data‑fusion techniques.
- Improve model robustness in real‑world environments.
- Integrate ML with firmware and hardware workflows.
- Mentor junior contributors.
Required
- Degree in Engineering, Physics, Mathematics or CS.
- Strong Python (NumPy, pandas, scikit‑learn).
- Experience with ML models (classification, regression, pattern recognition).
- Solid understanding of statistics and algorithms.
- Ability to work with sensor‑driven datasets.
- PyTorch or TensorFlow experience.
- Background in signal processing or spectral data.
- Exposure to embedded, IoT, or edge environments.
Required Skills
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