Position: Machine Learning Engineer/MLOps
Company: NCube
Category: Data Science
Experience required: 3y
English level: upper

Project — platform empowers global brands to deliver hyper-personalized communications to consumers, at scale. Data-driven, customer-centric approach accelerates engagement, brand value, and sales. Powered by machine learning, we turn existing data into an automated, consumer learning, and campaign execution process. Customer analysis, purchase prediction is future of retail business. How to influence and customer to buy exactly what you need. This project endorsed by Microsoft ventures and the Bridge Coca Cola program..

**Requirements:**
Hands on experience with  (or at least 3 years of TensorFlow) — must
Deep experience working on AWS infrastructure — must
Solid experience with advanced analytics/ML modelling/visualization tools
Strong programming skills in Python and SQL
Experience in applying MLOps; operating and deploying ML models in production. Comfortable with *nix, git
Experience with large-scale data infrastructures, including columnar data stores
Fluent in English: be able to articulate requirements and make proactive recommendations internally with the data science team and externally with client teams. Experience creating visualizations in the context of ML and/or statistical inference

**Good to have:**

NVTabular — big advantage
E Ray, PySpark / EMR
Analyst mentality: get excited about understanding the meaning, mapping the tables, and loading data from complex databases to simplify our machine learning engine data processes

**Responsibilities:**
Design of evaluation pipelines: design and implement monitoring processes and scripts to test ML prediction accuracy
Use MLOps tools and AWS infrastructure to validate, deploy and monitor models
Automation of code delivery, release cycle configuration and CI/CD
Load data and run: write SQL queries to load relevant data into monitoring processes and run the models to showcase accuracies results
Visualize: design and implement time series visualizations to communicate accuracy results across multiple data segmentations and product selections
Communicate accuracy metrics status and recommendations effectively and proactively, both internally and externally with enterprise level engineers and executives (both internally and client side)

*We offer:**

Competitive salary with the regular review
Flexible working schedule, fully remote work opportunities, office in the very center of Kyiv
PE 5% Taxes compensations, accountant assistance
Vacation (up to 20 working days)
Paid sick leaves (10 working days)
Medical Insurance after probation period (3 months)
Online English courses
Direct cooperation with the customer
Teambuildings, corporate parties and company trips abroad
Great working environment and team spirit