Machine Learning Research Engineer

**Machine Learning Research Engineer (Predictive Maintenance)**:
**Job description**

**Role**:Machine Learning Research Engineer (Predictive Maintenance)
**Location**:Singapore
**Term**:Full-time

**Reporting to**:Chief Technical Officer (CTO)

**About Datakrew**

Datakrew is an innovative deep technology company with strong roots in IoT, AI & data security founded by industry veterans and PhDs. We are headquartered in Singapore, with a regional presence in India, Indonesia, and Abu Dhabi. We are venture-backed by leading investors from Japan, Singapore, USA, and India. At Datakrew, we are building a no-code IoT platform with the tools for companies to develop, deploy and manage omnichannel enterprise IoT solutions rapidly i.e., within 48 hours Secure and robust IoT solutions built on our platform have been deployed in multiple sectors - such as Energy, Manufacturing, Maritime, Buildings, Transportation, etc. The solutions range across asset tracking, condition monitoring, energy management, predictive maintenance, performance warnings, decision insights, etc.

Today, our team has a combined experience of over 100 years in the IoT, AI, and cybersecurity space, and we are excited to grow our family as we embark upon a journey to transform ourselves from an IoT/AI startup to an industry leader within this decade. “By 2030, 25% of the world’s IoT data will flow through Datakrew” - this is our goal.

**The Product You Will Work On (AIStudio and Predictive Maintenance)**

Additionally, Datakrew is aiming to provide industrial predictive maintenance and monitoring solutions that are reliable and cost-effective.

As we scale rapidly, we are looking to bring on board a creative and proactive person who has experience and knowledge in machine learning, vibration data analysis, and predictive maintenance. This individual should take initiative, possess foresight, and should have a natural desire to take on challenges through innovative and unconventional methods, for they will be pivotal to the success of the company.

**Your Roles and Responsibilities**
- Work with the software and machine learning team members to develop the AI Studio App.
- Design, implement and evaluate machine learning experiments.
- Create documentation for the features implemented.
- Work with Airflow to create and schedule data pipelines or workflows used in AIStudio.
- Create DAGs required for the implementation of AIStudio and also develop the necessary APIs required for communication.
- Work and test different databases to find the best database for each use case.
- Create custom python libraries.
- Experiment with different predictive maintenance algorithms on machine vibration data from rotating equipment such as motors, pumps, turbines, compressors, gearboxes, etc.
- Perform FFT vibration analysis and understand the different types of data and the different techniques used to perform predictive maintenance.
- Automate fault detection algorithms for misalignment, eccentricity, load imbalance, cavitation, bearing failure, impeller issues, and looseness.
- Develop fault preemptive algorithms for faults developing in machines by analyzing frequency domain waterfall plots.
- Use software engineering best practices to ensure a high standard of quality for all of the above activities.
- Put together a roadmap for designing and implementing projects you are working on.
- Participate in code and design reviews to maintain our high development standards.

**Required Experience with Machine Learning and Software Engineering**
- Worked with various general machine learning and deep learning algorithms.
- Worked with time-series data and with machine learning algorithms related to time series data like time series forecasting and ARIMA models.
- Have experience in working with various databases like MongoDB and Postgres.
- Must have a good understanding of how to work with different frameworks like flask and have experience in writing various APIs.
- Strong background and experience in Python, and a solid understanding of MATLAB.
- Knowledge of three or more machine learning frameworks among Numpy, Scipy, Scikit-learn, Theano, TensorFlow, Keras, and PyTorch.
- Experience with development environments: e.g. Git or AWS.
- Have experience working with huge data sets.

**Required Experience with Predictive Maintenance**
- Should have experience working with rotating machine vibration datasets.
- Hands-on experience working with different algorithms for fault prediction and anomaly detection.
- Digital Signal Processing knowledge of commonly used Transforms such as CTFT, DTFT, DFT, FFT, Z-Transform, Bilinear Transform, DCT, Haar Transform, etc.

**Required Generic Software Aptitude and Qualifications**
- Bachelor’s degree or equivalent in any relevant discipline.
- Mandatory specialized knowledge in Machine Learning.
- Strong written and verbal communications skills in English to engage a variety of large audiences, internally and externally.
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