Mlops Engineer In Saas Resume Example
Professional ATS-optimized resume template for Mlops Engineer In Saas positions
John Doe
MLOps Engineer | CloudAI SaaS Solutions, San Francisco, CA
Email: example@email.com | Phone: (123) 456-7890
PROFESSIONAL SUMMARY
Innovative MLOps Engineer with over 5 years of experience designing and deploying scalable machine learning solutions in SaaS environments. Specialized in automating end-to-end ML pipelines, optimizing CI/CD workflows, and maintaining robust ML infrastructure. Adept at integrating cloud-native tools, managing CI/CD for ML models, and fostering collaboration between data science and DevOps teams. Passionate about leveraging automation and monitoring innovations to ensure high availability, security, and compliance of ML services.
SKILLS
Hard Skills
- ML Model Deployment & Scaling (Kubernetes, Docker, Helm)
- CI/CD Pipelines (Jenkins, GitLab CI, Argo CD)
- Cloud Platforms (AWS, GCP, Azure)
- Infrastructure as Code (Terraform, CloudFormation)
- MLOps Frameworks (Kubeflow, MLflow, TFX)
- Data Engineering & ETL Processes
- Model Monitoring & Drift Detection (Prometheus, Grafana, Evidently)
- Python, Bash, Go
- Version Control (Git, GitHub, GitLab)
Soft Skills
- Cross-Functional Collaboration
- Problem Analytical Thinking
- Agile Methodologies
- Communication & Documentation
- Continuous Learning & Innovation
WORK EXPERIENCE
June 2022 – Present
- Spearheaded the migration of ML workflows to Kubernetes, improving deployment speed by 40% and reducing downtime.
- Developed automated CI/CD pipelines using GitLab CI, integrating model validation, testing, and deployment, enabling faster iteration cycles.
- Implemented model monitoring solutions with Prometheus and Grafana, leading to proactive detection of model drift, increasing model reliability.
- Led cross-team collaboration to integrate ML pipelines with SaaS platform infrastructure, enhancing onboarding time and operational efficiency.
*Machine Learning Infrastructure Engineer | DataWave Inc, New York, NY*
July 2019 – May 2022
- Managed scalable ML model deployment using TFX pipelines on GCP, decreasing deployment errors by 25%.
- Created Terraform templates for cloud infrastructure as code, ensuring repeatable, secure environments for experimentation and production.
- Designed and maintained real-time data ingestion pipelines with Apache Beam and Kafka, improving data freshness for ML models.
- Collaborated with data scientists to develop version-controlled ML workflows, standardizing model reproducibility.
*Software Engineer, AI Infrastructure | TechBuild Labs, Remote*
Jan 2017 – June 2019
- Built containerized environments using Docker, enabling seamless deployment of ML models across cloud and on-premise systems.
- Automated resource provisioning, monitoring, and logging with custom scripts integrating with cloud APIs.
- Enhanced model validation scripts, reducing inconsistencies between training and production environments.
EDUCATION
**Bachelor of Science in Computer Science**
University of California, Berkeley
2013 – 2016
CERTIFICATIONS
- Certified Kubernetes Administrator (CKA) – 2024
- Google Professional Machine Learning Engineer – 2023
- DevOps Foundation Certification – 2022
PROJECTS
- **Automated ML Deployment Framework:** Designed an end-to-end framework utilizing Argo CD and Kubeflow to streamline deployment workflows, reducing manual intervention by 60%.
- **Real-Time Model Monitoring Dashboard:** Developed a Grafana-based dashboard integrating Prometheus metrics and Evidently AI to visualize model performance metrics, enabling rapid detection of data drift.
- **Serverless Data Processing Pipelines:** Built serverless ETL pipelines using GCP Dataflow and Cloud Functions, facilitating near real-time data ingestion for predictive models.
TOOLS & TECHNOLOGIES
- Kubernetes, Docker, Helm, Argo CD
- AWS (EKS, Lambda, S3, CloudWatch), GCP (Vertex AI, Dataflow, Cloud Monitoring)
- Terraform, CloudFormation
- ML Frameworks: TensorFlow, PyTorch, TFX, MLflow
- CI/CD: Jenkins, GitLab CI, Drone
LANGUAGES
- English (Fluent)
- Spanish (Professional Working Proficiency)
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