Remote DevOps Engineer for AI Applications (Fluent Ukrainian or English)

Description:

• We are seeking a dynamic and innovative DevOps Engineer for AI Applications who thrives on turning complex challenges into seamless solutions and is passionate about driving the future of AI in production environments.
• The role involves creating cutting-edge products and pioneering new features to revolutionize how machine learning models are deployed, monitored, and maintained at scale.
• The product is a solution created to automate support (text communication) for popular CRM systems using machine learning and is currently in production.
• The team consists of an experienced CEO & CTO with a background in Data Science and Machine Learning, Front-End and Back-end developers, a Machine Learning Engineer, a Marketing Manager, and a Designer.
• Responsibilities include deploying and maintaining AI applications in production environments, designing and implementing CI/CD pipelines, monitoring system performance, collaborating with ML engineers and data scientists, managing infrastructure using containerization and orchestration tools, and ensuring security and compliance standards are met in all deployments.

Requirements:

• Candidates must have 2.5-3 years of commercial experience in a related role, preferably with experience in AI application deployment.
• Hands-on experience in deploying and maintaining AI applications in production environments is required.
• Proficiency with containerization technologies, such as Docker, and orchestration tools like Kubernetes is necessary.
• Experience with monitoring and logging tools, such as Prometheus, Grafana, or the ELK Stack is essential.
• A strong knowledge of CI/CD pipelines and tools, like Jenkins or GitLab CI/CD, to automate deployment processes is needed.
• Candidates should have experience with at least one major cloud platform, such as AWS, Azure, or Google Cloud.
• Solid scripting skills using languages like Bash and Python for automation tasks are required.
• An understanding of infrastructure as code (IaC) tools, such as Terraform or CloudFormation, is necessary.
• Familiarity with configuration management tools, like Ansible, Chef, or Puppet is important.
• Proficiency in Git and understanding of branching, merging, and pull requests is required.
• A basic understanding of MLOps practices and tools, such as MLflow or Kubeflow, is a plus.
• Experience with cloud-based ML services, like AWS SageMaker, Azure ML, or Google AI Platform, is advantageous.
• Strong problem-solving skills and the ability to work collaboratively in a team environment are essential.
• Additional qualifications that would be a plus include experience with distributed computing frameworks (e.g., Apache Spark), knowledge of model interpretability and explainability techniques, familiarity with automated testing and quality assurance practices for ML models, exposure to data engineering concepts and tools, and a good sense of humor.

Benefits:

• The position offers compensation in USD.
• Remote work is available in Ukraine or in a similar time zone.
• The company provides adequate, friendly management with no bureaucracy.
• Employees can enjoy a cozy startup atmosphere with stability from a holding company.
• There will be plenty of interesting talks and communication with the team.