DevOps (offline)

Requirements:
• 3+ years of work experience as a DevOps, Build and Release Engineer, or Site Reliability Engineer;
• Strong experience with Kubernetes and Docker (2+ years preferred);
• Knowledge of CI & CD practices and supporting tools;
• Experience with automating deployment, scaling, and management of Container applications;
• Experience with Linux, Open Source tooling, and cloud platforms such as Amazon AWS, Microsoft Azure, and Google cloud platform;
• Excellent troubleshooting and problem-solving abilities;
• Type S(startup) personality: smart, ethical, friendly, cross-functional, hardworking, and proactive

Will be a plus:
• Knowledge of at least one development language, such as Python or Ruby;
• B.S. in Computer Science, Electrical Engineering, Computer Engineering or equivalent.

We offer:
• Competitive compensation depending on experience and skills;
• Opportunities for self-realization, professional and career growth;
• Compensation package (paid vacation, sick leaves), flexible working hours;
• English classes

Responsibilities:
• Continually improve DevOps tools, processes, and procedures;
• Build, maintain, and scale infrastructure for Production and Staging environments;
• Deploy, manage, and support our environments, including troubleshooting of incidents;
• Design automation frameworks, tools, and systems through continuous integration and continuous deployment that deliver the company’s software into Staging and Productions environments in a very fast-paced environment;
• Work closely with Development and QA teams to help ensure end-to-end quality;
• Work with third-party vendors to resolve infrastructure issues;
• Learn new technologies, architect, and implement new solutions to automate infrastructure;
• Bring innovative ideas and solve complex technology problems.

About project:
The project is a full-stack data science platform that helps enterprises manage and scale AI. Its collaborative end-to-end solution enables companies to accelerate innovation and build high-impact machine learning models. From Fortune 500 companies to startups, this solution helps data scientists solve complex problems, by building intelligent machines. The platform is used across industries by leading companies in finance, gaming, BI, automotive, manufacturing, e-commerce and more.

In this exciting role, you’ll be working with the latest technologies and will be responsible for deploying a data science platform to leading companies both cloud and on-premise. You will deploy updates, interact with customers and manage CI/CD.