2,5+ years of software development experience;
Python and basic libraries for machine learning such as Scikit-Learn and Pandas;
Proficiency with frameworks such as TensorFlow, Keras, Spark or Caffe;
Hands on experience with AWS and cloud-based computing environments, including technologies like EMR and S3;
Experience with MongoDB and PostgreSQL;
You can speak English at the Intermediate level (at least).
Experience in deploying machine learning models to production;
Understanding of multiple machine learning algorithms like Support Vector Machines, Random Forests, and Neural Networks;
Expertise in visualizing and manipulating big datasets for exploratory data analysis.
Work with interesting large-scale US project, one of the market leaders in the field and great professional team;
Flexible work schedule;
Friendly and engaging professional team;
Environment open for professional growth;
Compensation of sports;
Medical service;
Kicker and other relaxing activities;
Regular corporate events;
Nice office with beautiful kitchen and delicious buffet at the business center :)
Explore algorithms that could be used to solve a given problem and making tradeoffs depending on different metrics;
Manage the machine learning model lifecycle from the development stages to the iteration and improvement process once the model is live;
Architect scalable and reliable machine learning services to process production data in nearly real-time;
Help evaluate new tools and technologies to keep the technology stack at the cutting edge;
Help debug critical issues in complex microservice architectures.
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The stack of technologies: Python (also NodeJS and Java), TensorFlow, Keras, Spark, Caffe, AWS (EMR, S3), MySQL, PostgreSQL.