Mlops Engineer In Cloud Resume Example
Professional ATS-optimized resume template for Mlops Engineer In Cloud positions
Jane Doe
MLOps Engineer | Cloud & AI Infrastructure Specialist
Email: jane.doe@example.com | Phone: (123) 456-7890 | LinkedIn: linkedin.com/in/janedoe | GitHub: github.com/janedoe
PROFESSIONAL SUMMARY
Dynamic MLOps Engineer with over 5 years of experience building scalable, reliable machine learning pipelines in cloud environments. Adept at deploying, monitoring, and managing end-to-end ML workflows utilizing Kubernetes, Docker, and cloud-native tools. Skilled in CI/CD automation, model versioning, and optimizing ML deployments for latency and cost-efficiency. Passionate about driving AI maturity in organizations through robust infrastructure design, automation, and collaborative development practices.
EDUCATION
**Bachelor of Science in Computer Science**
Massachusetts Institute of Technology (MIT), Cambridge, MA
*Graduated: 2017*
CERTIFICATIONS
- **AWS Certified Machine Learning – Specialty** (2023)
- **Kubernetes Application Developer (CKAD)** (2024)
- **Google Cloud Professional Data Engineer** (2022)
PROJECTS
Automated ML Model Deployment Platform
Developed an end-to-end deployment system integrating TensorFlow Serving with Kubernetes, enabling data science teams to push models via GitOps workflows. Reduced manual deployment errors and improved deployment speed from hours to minutes.
Real-Time Model Monitoring & Drift Detection System
Implemented with Evidently AI and custom Grafana dashboards, this system continuously tracks model performance metrics in production, triggering alerts upon degradation, which led to quicker model retraining cycles and better accuracy retention.
LANGUAGES
Python, Bash, Go
*References available upon request.*
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