Remote (Fluent Ukrainian) DevOps Engineer (deploying AI apps)

Description:

• Seeking an ambitious and creative DevOps Engineer who is passionate about AI, enjoys complex challenges, and is ready to implement innovative solutions in the field of artificial intelligence.
• The product is designed to automate support (text communication) for popular CRM systems using ML and is already launched in production.
• The team includes 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 building and maintaining ML infrastructure, supporting deployment and monitoring of ML models in production, collaborating with Data Scientists and Software Engineers for smooth integration of ML models, implementing and maintaining CI/CD pipelines for ML projects, resolving performance and deployment issues related to ML models, updating documentation, and influencing project strategy.

Requirements:

• 1-1.5 years of commercial experience in a related role (e.g., ML Engineer, Data Engineer, DevOps Engineer).
• Practical experience in deploying and supporting ML models in production.
• Experience with monitoring and logging tools (e.g., Prometheus, Grafana, ELK Stack).
• Working experience with popular ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Proficient in Python and scripting languages (e.g., Bash).
• Experience with major cloud platforms (e.g., AWS, Azure, Google Cloud).
• Basic understanding of MLOps practices and tools (e.g., MLflow, Kubeflow).
• Knowledge of CI/CD pipelines and tools (e.g., Jenkins, GitLab CI).
• Understanding of containerization technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes).
• Familiarity with cloud ML services (e.g., AWS SageMaker, Azure ML, Google AI Platform).
• Strong skills in using Git and understanding branching, merging, and pull requests.
• Plus: experience with distributed computing frameworks (e.g., Apache Spark), knowledge of model interpretability techniques, familiarity with automated testing and quality assurance practices for ML models, understanding of data processing concepts and tools (e.g., ETL processes, data storage), and a sense of humor.

Benefits:

• Competitive compensation in USD.
• Opportunity to influence the product architecture.
• Variety of interesting tasks and communication with the team.
• Supportive and friendly management with no bureaucracy.
• Remote work in Ukraine or within a close time zone.
• Atmosphere of a cozy startup with stability from a holding company.