Sensemore is positioned to leverage machine health monitoring technologies around the world. At Sensemore, we are enthusiastic about finding out new technologies, and we are looking for a team member who has this passion for learning and has a sense of responsibility. You will be working with our friendly team in the Magnet Office in ITU Maslak who’s looking forward to you exchanging their ideas.
Your main role will be developing world leading technologies to identify fault detection and analysis of industrial machines on a huge amount of dataset. You’ll research, develop and train machine learning models as well as comparing them with the state-of-the-art techniques.
- Supporting the existing ML/AI projects
- Designing, training and verifying machine learning models
- Generating synthetic data from real-world dataset
- Prototype new technologies to create proof of concept projects
- Translating a research paper into implementation
For this position what we are looking for;
- BS or MS in Computer Science, Electronics Engineering, Mathematics, Physics or a related discipline
- Excellent understanding of machine-learning, clustering and classification techniques, and their algorithms
- Strong programming skills in Python with model training, data analysis and visualisation for massive amounts of data
- Experience on Python scientific packages and frameworks such as Pandas, Scikit-learn, SciPy, NumPy, Jupyter, Matplotlib, Seaborn etc.
- Experience on one of the deep learning frameworks e.g. TensorFlow, Keras or PyTorch
- Knowledge and understanding on Matlab, C/C++
- Knowledge on digital signal processing (DSP)
- Familiarity with version control tools e.g. Git
- Proficiency in Linux environment
- Fluent professional-level English
It’s not required, but preferred, that you have:
- Experience on time series forecasting and time series analysis
- Experience on clustering/classification/anomaly-detection for time-series data applications
- Experience on Kaggle contest
- Practice on Cloud Platform’s machine learning Solutions (AWS Sagemaker)