Remote (Fluent Ukrainian or English) Data Scientist (MLOps, AI DevOps)

Description:

• Seeking a dynamic and innovative Data Scientist (MLOps, AI DevOps) to drive the future of AI in production environments.
• Responsible for building and maintaining ML infrastructure and pipelines.
• Support deployment and monitoring of ML models in production.
• Collaborate with data scientists and software engineers for smooth integration of ML models.
• Implement and maintain CI/CD pipelines for ML projects.
• Troubleshoot issues related to ML model performance and deployment.
• Contribute to documentation and best practices for MLOps processes.
• Product: Automation of support for popular CRM systems using ML, currently in production.
• Team includes experienced CEO & CTO, developers, ML Engineer, Marketing Manager, and Designer.

Requirements:

• 1-1.5 years of commercial experience in a related role (e.g., ML Engineer, Data Engineer, DevOps Engineer).
• Hands-on experience in deploying and maintaining machine learning models in production.
• Experience with monitoring and logging tools (e.g., Prometheus, Grafana, ELK Stack).
• Proficient in popular Machine Learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Solid experience with Python and scripting languages (e.g., Bash).
• Familiarity with at least one major cloud platform (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-based ML services (e.g., AWS SageMaker, Azure ML, Google AI Platform).
• Proficiency in using Git and understanding of branching, merging, and pull requests.
• Plus: Experience with distributed computing frameworks, model interpretability techniques, automated testing for ML models, data engineering concepts, and tools.

Benefits:

• Compensation in USD.
• Remote work in Ukraine or similar time zone.
• Adequate, friendly management with no bureaucracy.
• Cozy startup atmosphere with stability from a holding company.
• Plenty of interesting talks and communication with the team.