Position: Data science, Machine learning engineer, Machine learning researcher
Category: Data Science
English level: upper
Years of experience: 2

I've created the whole recommendation system along with the complementary systems (like trending algorithm, different KPIs and so on) from scratch. Starting from the research and finishing with deploying a complex system on production.
My experience is mainly related to construction of  recommendation systems at scale. Here is a list of things that I have experience with/were done by me.
- Created hybrid recommendation systems based on both catalog metadata and user activity data, using word2vec model (aka "related to" on YouTube).  
- Created personalized recommendation system using LSTM model.
- Made automatic ML lifecycle with hyper-parameters tuning, best model selection and model versioning (for all the systems).
- Created framework for algorithm evaluation and comparison (also including baseline algorithms) in terms of the following recommendation metrics : MAP (mean average precision), NDCG (normal cumulative gain) and Hit Ration.
- Implemented LinUCB (contextual bandit for personalized recommendations) as a solution for cold-start problem.
- Implemented many data pipelines using pandas and apache-druid.
- Have experience of working with Apache Druid, S3, redis.
- Implemented complementary algorithms like trending.
- Have partial experience of working with GCLOUD and AWS sagemaker.
- Have experience with Deep learning.

Other experience:
- Created real-time facial expression (with custom classes) and human body tracker which was then ported to Android using novel techniques for model compression. 
Used technologies : (SSD mobilenetV1, mobilenetV1, Yolo v3, knowledge distillation). 
- Created DS and ML course for new generation.  

 
Interests : Reinforcement learning, computer vision, natural language processing, generative models, bayesian modeling. 

What work I'm looking for:
Currently I'm interested in the position of machine learning engineer or machine learning researcher in the domain of recommendation systems/reinforcement learning (or any other sphere, the choice is more task related). I would like to make ad hoc research that will result in the solutions of a high quality + work in a team of professionals.
I want to find a work which will help me to improve both soft and hard skills. I'm eager to study new things, thus I would really like to face difficult and non-standard problems. I would also like to apply new machine learning algorithms and cutting-edge technologies to solve problems. I'm interested in the position of machine learning research or machine learning engineer.