ML Engineer - Applied Machine Learning

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

• 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.

Depending on Your Experience

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.

Mid‑Level (2–4 years)

• 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.

Requirements

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.

Nice to Have

• PyTorch or TensorFlow experience.
• Background in signal processing or spectral data.
• Exposure to embedded, IoT, or edge environments.