(Fluent Ukrainian or English) MLOps Engineer

August 16

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Description

• Assist in building and maintaining ML infrastructure and pipelines • Support the deployment and monitoring of ML models in production • Collaborate with data scientists and software engineers to ensure 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 the documentation and best practices for MLOps processes.

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 in monitoring and logging tools (e.g., Prometheus, Grafana, ELK Stack) • Experience with popular Machine Learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn) • Solid experience with Python • Experience with scripting languages (e.g., Bash) • Experience with at least one major cloud platform (AWS, Azure, Google Cloud) • Basic understanding of MLOps practices and tools (e.g., MLflow, Kubeflow) • Basic 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.

Benefits

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