You will be responsible for:
— Work as MLOps/DevOps Engineer with Data Scientists and RnD teams colaboration
— developing AWS SageMaker pipelines,
— automating ML AWS resources and infrastructure provisioning,
— developing ML oriented CI/CD pipelines,
— PyTorch, TensorFlow experience
— AWS SageMaker experience
— ML Ops experience (Airflow, Kubeflow)
— 1+ years of experience with any major cloud provider (AWS, GCP, Azure), preferably AWS
— Python experience
— experience with Infrastructure as code (Terraform, CloudFormation, etc.) is a plus
— experience with version control systems (Git or similar)
— Linux OS knowledge,
— basic networking knowledge,
— Intermediate English language proficiency,
— being a team player,
— be innovative, learn new tools, systems, and best practices, propose your own ideas,
— strong & confident communication skills.
— many stable projects — we always leave the option to change project/team,
— 100% payment for certifications (AWS, GCP, K8s, Jenkins, HashiCorp, etc.) with large bonuses for passing (you will pass exams only during working hours),
— internal and external seminars on current DevOps topics /+ exclusive sessions with invited AWS experts /, the opportunity to ask questions and share expertise.
— 20 paid days off/year, unlimited paid sick leave,
— financial bonuses for certifications completed,
— compensation for sports and English courses,
— Legal and accounting advice and support,
— In-house online English courses,
— relocation support program for all your family.
— pure DevOps focus — opportunity to work with cutting-edge DevOps tools and technologies in a team of high-end professionals,
— high income and specific personal growth/development plans,
— future vertical or horizontal personal development,
— fully paid professional certifications (AWS, GCP, K8s, Jenkins, HashiCorp, etc.),
— multiple fully paid educational resources: Udemy, Cloud Guru & Braincert, Tutorials Dojo,
— internal & external company workshops and presentations on various DevOps topics including exclusive sessions with AWS employed experts.