Requirements:
—Strong knowledge in machine learning fundamentals i.e. linear models, decision trees, naïve bayes, clustering algorithms(k-means, DBSCAN, SOM), dimensionality reduction(PCA, t-SNE) and a good grasp of the strengths and weaknesses of specific approaches. Good foundation in basic statistics and linear algebra.
—Strong Python knowledge;
—Comprehensive knowledge of the Python data analyses ecosystem (Pandas, Numpy, Scikit-learn etc.);
—At least minor experience with python visualization tools(matplotlib/seaborn, Plotly)
—Strong practical experience with Deep Learning frameworks like PyTorch, Tensorflow or Keras.
Would be a plus:
—Experience with R, C++
—Experience with following modern neural networks architectures: LSTM and other RNN-based, Tranformers(BERT etc.).
—Familiarity with time series predictive/anomaly detection analyses, natural language processing, signal processing
—Understanding SOTA approaches for machine learning problems like unsupervised/ s emi — super v ised l earning.
—Experience with the following DL frameworks: DLib, Darknet, Theano.
—Awareness of CRISP-DM process model
—Experience with continuous integration and release management tools, preferably within the AWS platform.
—Hands-on Experience with common architecture of MLOps system by the means of Hadoop, Docker, Kubernetes, cloud services and experience with managing production ML lifecycle.
With us you can:
Develop your technical knowledge:
— Use latest technologies
— Participate in technical events and conferences (the cost is covered by the company)
— Regular techtalks and professional development
Improve your soft skills:
— Build strong teamwork skills and become an essential part of the dynamic teams
— Improve your English at classes and speaking directly with clients
— Increase your productivity and communication level via Scrum, Kanban, Agile methodologies
What else do we offer?
— Competitive compensation and benefits
— Flexible and negotiable schedule
— Nice and comfortable office located near metro station
— Covered rest period (20 business days)
— Free English classes (we have 3 teachers in our team)
— English Movie Fridays
— Break area with Xbox, air hockey, ping-pong and table soccer
— Truly friendly atmosphere and unforgettable events
— Bookcrossing
— Basketball and ping-pong teams
— Build advanced Machine Learning models and improve the accuracy of those models.
— Deploy the models in production where it will serve customers in real time.
— Test validate and deploy algorithms into production ready status.
— Ensure models maintain explain-ability to make decisions and choices around predictions and impact on the business.
— Design and build next-generation machine learning frameworks.
— Integrate Machine Learning algorithms with other applications and services.
— Apply algorithms to business and improve customer experience.
— Create operational efficiency and make recommendations as to best algorithms to use for different use cases.
We are looking for a Machine Learning Engineer to drive and develop the direction of Machine Learning in CHI Software.