Mlops Engineer in Fintech

Hard Skills

- MLOps & Model Lifecycle Management (MLflow, Kubeflow, TFX)

- Cloud Platforms (AWS, GCP, Azure)

- Containerization & Orchestration (Docker, Kubernetes)

- CI/CD Pipelines (Jenkins, GitHub Actions, GitLab CI)

- Data Engineering & ETL Processes

- Model Deployment & Monitoring (Prometheus, Grafana, Seldon)

- Security & Compliance (GDPR, PCI DSS)

- Programming (Python, Bash, SQL)

- Version Control & CI/CD Automation

- API Development & Microservices Architecture

Soft Skills

- Cross-functional Collaboration

- Analytical Problem Solving

- Agile Project Management

- Continuous Improvement & Adaptability

- Communication & Technical Documentation

- Stakeholder Engagement

*Senior MLOps Engineer*

*Fintech Solutions Inc., New York, NY*

June 2022 – Present

- Led the migration of ML models from development to production across multiple domains including risk assessment and fraud detection, reducing deployment time by 40%.

- Designed and implemented a scalable CI/CD pipeline utilizing GitHub Actions and Kubernetes, improving model update frequency while ensuring compliance.

- Developed real-time model performance dashboards leveraging Prometheus and Grafana, enabling proactive identification of drift and anomalies.

- Collaborated with data scientists to automate model retraining pipelines, decreasing manual intervention by 60%.

*MLOps Engineer*

*SecurePay Fintech, San Francisco, CA*

August 2019 – May 2022

- Built and maintained end-to-end ML pipelines for credit scoring, achieving 99.9% uptime and reducing latency by 30% via optimized deployment strategies.

- Managed containerized environments with Docker and Kubernetes, supporting rapid scaling during high-transaction periods.

- Integrated model versioning and lineage tracking through MLflow, facilitating auditability for compliance audits.

- Implemented security protocols for data encryption and access controls, aligning with GDPR and PCI DSS standards.

*Data Engineer & AI Developer*

*FinEdge Analytics, Remote*

July 2017 – July 2019

- Developed ETL workflows to prepare large datasets for machine learning models, streamlining data ingestion from multiple financial data sources.

- Initiated migration of analytics workloads to GCP’s AI Platform, enhancing collaborative model training capabilities.

- Collaborated with ML teams to automate feature extraction processes, resulting in faster model iteration cycles.

**Bachelor of Science in Computer Science**

University of California, Berkeley

*September 2013 – June 2017*

- Google Cloud Professional Machine Learning Engineer

- AWS Certified Machine Learning – Specialty

- Certified Kubernetes Administrator (CKA)

- DataRobot Automated Machine Learning Certification

Automated Fraud Detection System

- Designed a scalable MLOps framework integrating TensorFlow Extended (TFX) on GCP, enabling continuous training and deployment of fraud detection models with real-time monitoring.

Credit Risk Modeling Pipeline

- Developed a microservices architecture for credit scoring, utilizing Docker, Kubernetes, and CI/CD pipelines to facilitate agile model updates while maintaining compliance standards.

- **ML Frameworks:** TensorFlow, PyTorch, Scikit-learn

- **Platforms:** GCP, AWS, Azure

- **Orchestration:** Kubernetes, Docker Swarm

- **Pipeline Tools:** MLflow, Kubeflow, TFX, Airflow

- **Monitoring:** Prometheus, Grafana, Seldon

- **Coding:** Python, Bash, SQL

- English (Native)

- Spanish (Professional Working Proficiency)