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About IntelliThink IntelliThink builds industrial machine-health and predictive-maintenance solutions using sensor data, signal processing, and machine learning. Our platform analyzes vibration, electrical current, and other machine signals to detect abnormalities, identify faults, and improve equipment reliability. The Role We are looking for a Python Data Engineer to build data pipelines, signal-processing algorithms, and ML-based analytics for industrial machine-health applications. You will work with high-frequency time-series and waveform data from vibration, electrical current, and other machine sensors, collaborating with condition-monitoring experts and the product engineering team. Key Responsibilities Build Python pipelines for high-frequency sensor and time-series data.Process vibration, current, and time-waveform signals.Implement FFT, filtering, spectral analysis, envelope analysis, and feature extraction.Develop algorithms for anomaly detection and machine fault identification.Build and evaluate ML models for anomaly detection and fault classification.Develop analytical APIs and backend services using FastAPI or Flask.Integrate analytics and ML models with IntelliThink's predictive-maintenance platform.Work with domain experts to translate machine-diagnostic knowledge into scalable algorithms. Required Skills 36 years of Python development, data engineering, or related experience.Strong knowledge of Python, SQL, NumPy, SciPy, Pandas, and Git.Experience working with time-series, waveform, or sensor data.Understanding of FFT, filtering, sampling, spectral analysis, and feature extraction.Experience with PostgreSQL, TimescaleDB, InfluxDB, or similar databases.Understanding of ML concepts such as classification, clustering, and anomaly detection.Experience with scikit-learn or similar ML frameworks.Strong analytical and problem-solving skills. Good to Have Vibration analysis, condition monitoring, or Motor Current Signature Analysis (MCSA).Wavelets, order tracking, envelope analysis, or advanced signal processing.XGBoost, LightGBM, PyTorch, or TensorFlow.FastAPI, Flask, Docker, MQTT, Modbus, or OPC-UA.Experience in Industrial IoT, rotating machinery, or predictive maintenance. What We're Looking For A strong Python engineer who enjoys working with signals, data, and algorithms. Prior vibration-analysis experience is an advantage but not essentialwe're looking for someone who can combine data engineering, signal processing, and machine learning to solve real-world industrial problems. .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.