Machine Learning Engineer
Reviewing state-of-the-art machine learning & deep learning technologies for analysis of biosignals.
Writing robust data pipelines for:
feature engineering and data modelling
model hyperparameter optimization
model evaluation and explainability
model training, deployment and automated retraining
model version tracking & governance
data archival & version management
model and drift monitoring
Improving readability and efficiency of the code.
Writing documentation, tests and visualizations whenever necessary.
MSc or (preferably) PhD in Computer Science, Mathematics, Statistics, Bioinformatics, Biostatistics, Computational Neuroscience or similar.
In-depth knowledge of statistics and machine learning concepts. Expertise in signal processing and deep learning is also strongly recommended.
Proven experience in machine learning projects, in particular, experience with predictive models based on time-series data from sensors.
Good software engineering skills and the ability to productize models.
Proficiency in Python and knowledge of machine learning (scientific) libraries/frameworks such as Sklearn, Scipy, Numpy, Pandas, Tensorflow, Pytorch.
Interest in human physiology, medicine, and wellness.
Scientific track record, i.e. papers published in machine learning or similar - conferences.
Participation in Kaggle.
nice to have
Knowledge of Matlab and previous experience with analysis of bio-signals (ECG, EEG, PPG).
Opportunity to co-create meaningful technology and products that improve people’s lives.
Culture of ownership, openness and trust.
Working with professionals in a small dream team.
The most effective and proven cooperation methodologies and tools.
Freedom and flexibility working remotely or on-site in Wroclaw, Poland.
Unlimited, paid vacation time.
Work equipment and tools of your choice.
Competitive and fair salary depending on skills and experience.
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