Machine Learning Engineer for Predictive Maintenance

axon pulse Israel
Relocation
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AI Summary

We're hiring a Machine Learning Engineer to work on predictive maintenance with sensor and time-series data. The role involves data ingestion, feature extraction, anomaly and degradation detection, model training, evaluation, and turning results into practical tools for engineering teams. The ideal candidate has strong Python and applied machine learning experience, with a background in Computer Science, Electrical Engineering, or related fields.

Key Highlights
Predictive maintenance with sensor and time-series data
Data ingestion, feature extraction, and model training
Anomaly and degradation detection, model evaluation, and practical tool development
Key Responsibilities
Data ingestion
Feature extraction
Anomaly and degradation detection
Model training
Evaluation
Turning results into practical tools for engineering teams
Technical Skills Required
Python Applied machine learning Time-series data Sensor data Signal processing Anomaly detection Forecasting Degradation modeling
Benefits & Perks
Relocation package provided
Flexible work arrangement
Opportunity to work with noisy or partially labeled data
Nice to Have
Predictive maintenance experience
Condition monitoring experience
Diagnostics experience
Prognostics experience
RUL experience
MLOps experience
Dashboard experience
API experience
Edge deployment experience

Job Description


We’re hiring a Machine Learning Engineer to work on predictive maintenance with sensor and time-series data.


This role is for someone who likes messy real-world data, understands that models are only part of the job, and can build things that engineers can actually use.


The work includes data ingestion, feature extraction, anomaly and degradation detection, model training, evaluation, and turning results into practical tools for engineering teams.


What we’re looking for:

* B.Sc. or M.Sc. in Computer Science, Electrical Engineering, Mechanical Engineering, Data Science, Applied Mathematics, Physics, or a related field

* Strong Python and applied machine learning experience

* Experience with time-series data, sensor data, signal processing, anomaly detection, forecasting, or degradation modeling

* Ability to work with noisy or partially labeled data

* Experience building ML workflows beyond notebooks

* Clear technical communication

* Flexibility to travel domestically and internationally when needed for customer meetings, field work, or integration activities

*Option for Relocation


Nice to have:

* Experience in predictive maintenance, condition monitoring, diagnostics, prognostics, or RUL

* Work with vibration, acoustic, temperature, pressure, current/voltage, or other industrial sensor data

* Experience with MLOps, dashboards, APIs, or edge deployment

* Background in hardware, industrial, aerospace, automotive, or defense systems


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