AI & DATA · LAHORE, PAKISTAN / REMOTE · FULL-TIME
ML Engineer — Predictive Maintenance
You will build the models that tell a plant a bearing will fail before it does. The inputs are vibration, temperature, current, and work-order history from our own sensors; the output is a prediction a maintenance planner can trust. Accuracy here is not a leaderboard number — it is avoided downtime.
What you will do
- Develop and productionize failure-prediction and anomaly-detection models on multivariate sensor time series.
- Build training and evaluation pipelines that handle noisy, imbalanced, real-world industrial data.
- Work with firmware and backend teams on feature extraction at the edge versus the cloud.
- Define honest evaluation: precision-recall trade-offs, lead-time metrics, and calibration that operations teams can act on.
- Feed model outputs into agent workflows with human-in-the-loop controls and clear explanations.
What you bring
- 3+ years applying machine learning in production, ideally on time-series or sensor data.
- Strong Python and experience with the standard ML stack; solid grasp of classical methods, not just deep learning.
- Understanding of signal processing (FFT, spectral features) or willingness to learn it quickly.
- Rigor about evaluation and failure modes; you would rather ship a calibrated simple model than an impressive uncalibrated one.
- Ability to explain model behavior to non-ML colleagues and customers.
Apply for this role
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