Exciting opportunity for an Entry-Level MLOps Engineer! Join us in building and maintaining ML infrastructure and deployment pipelines.
**Responsibilities:**
• Support ML model deployment and monitoring
• Assist in building ML pipelines and infrastructure
• Help automate ML workflows
• Monitor model performance and data quality
• Collaborate with data scientists and engineers
• Participate in DevOps and MLOps best practices
**Requirements:**
• Bachelor's degree in Computer Science, Software Engineering, or related field
• Understanding of machine learning concepts
• Basic DevOps knowledge (CI/CD, containers)
• Programming skills in Python
• Familiarity with version control (Git)
• Problem-solving and troubleshooting abilities
**Technical Skills:**
• Python programming
• Basic ML understanding
• Docker and containerization
• CI/CD concepts
• Linux/Unix systems
• Cloud platforms (AWS, GCP, or Azure)
**Nice to Have:**
• Experience with Kubernetes
• Knowledge of MLOps tools (MLflow, Kubeflow)
• Understanding of monitoring and logging
• Exposure to infrastructure as code (Terraform)
• Experience with ML frameworks (PyTorch, TensorFlow)
**What We Offer:**
• Learn cutting-edge MLOps practices
• Work with modern ML infrastructure
• Mentorship from experienced engineers
• Hands-on experience with cloud platforms
• Career growth in MLOps field