Mlops Engineer in Cybersecurity

Hard Skills

- MLOps Pipeline Development (Kubeflow, MLflow, Airflow)

- Containerization & Orchestration (Docker, Kubernetes)

- Cloud Platforms (AWS, Azure, GCP)

- CI/CD Automation (Jenkins, GitOps)

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

- Cybersecurity ML Techniques (Anomaly Detection, Deep Learning for Threat Detection)

- Data Engineering (Spark, Kafka, ELK Stack)

- Programming (Python, Bash, Go)

- Version Control & Code Quality (Git, DataLad)

Soft Skills

- Cross-functional Collaboration

- Problem Solving in High-Pressure Environments

- Technical Documentation & Knowledge Sharing

- Agile & Scrum Methodologies

- Continuous Learning & Adaptation

- Cybersecurity Best Practices and Compliance

*Senior MLOps Engineer – Cybersecurity*

*CyberSecure Solutions, Remote*

June 2022 – Present

- Architected and maintained scalable ML pipelines for real-time threat detection, reducing false positives by 25%.

- Integrated ML models with SIEM systems, enabling automated anomaly classification from network logs and endpoint data.

- Led migration of deployment workflows to Kubernetes on AWS EKS, resulting in 40% reduction in model deployment time.

- Established model governance procedures, including versioning, drift detection, and audit trails in compliance with GDPR and ISO27001 standards.

- Collaborated with cybersecurity analysts to refine detection algorithms, incorporating zero-day threat signatures.

*Machine Learning Operations Engineer*

*SecureTech Labs, San Francisco, CA*

August 2019 – May 2022

- Streamlined model training, testing, and deployment workflows, reducing cycle time from weeks to days using CI/CD pipelines.

- Developed automated monitoring dashboards in Grafana for detecting model performance degradation during live operations.

- Optimized ML infrastructure with GPU-accelerated instances, improving model training speed by 35%.

- Implemented data pipelines with Kafka for ingesting streaming security logs, enabling proactive threat response.

- Conducted security assessments of AI models, mitigating vulnerabilities like model inversion and adversarial attacks.

Data Scientist (Entry-level)

*Innovo Cyber Defense, Boston, MA*

July 2017 – July 2019

- Designed anomaly detection algorithms for network traffic analysis, contributing to early breach detection initiatives.

- Assisted in data pipeline setup from raw log data to feature extraction, improving data readiness by 20%.

- Provided insights through visualizations that informed cybersecurity policy decisions.

**Master of Science in Data Science**

Massachusetts Institute of Technology (MIT), Cambridge, MA

*2015 – 2017*

**Bachelor of Science in Computer Science**

University of California, Berkeley, CA

*2011 – 2015*

- **AWS Certified Machine Learning – Specialty** (2023)

- **Certified Kubernetes Application Developer (CKAD)** (2022)

- **GCP Professional Machine Learning Engineer** (2023)

- **Cybersecurity & Data Privacy Certification** – (ISC)² (2021)

ThreatHunter AI Platform

- Developed an AI-powered threat hunting platform utilizing unsupervised learning algorithms for detecting novel attack patterns.

- Deployed on GCP using Container-Optimized OS with Terraform, ensuring high availability and scalability.

- Enabled security analysts to proactively identify and investigate zero-day vulnerabilities.

Automated Incident Response Framework

- Built an automated pipeline that correlates alerts and generates incident reports, reducing response times by 60%.

- Integrated with SIEM and SOAR platforms, enhancing real-time defense capabilities in client networks.

- **ML & Data Engineering:** TensorFlow, PyTorch, Spark, Kafka, Elasticsearch

- **MLOps Platforms:** Kubeflow, MLflow, DataRobot, Azure ML

- **Cloud Computing:** AWS (S3, Lambda, EKS), GCP (GKE, Vertex AI), Azure (ML Services)

- **Containerization & Orchestration:** Docker, Kubernetes, Helm

- **Monitoring & Logging:** Prometheus, Grafana, DataDog, ELK Stack

- **Version Control & CI/CD:** Git, Jenkins, GitOps, Argo CD

- Python (Expert)

- Bash (Advanced)

- Go (Intermediate)

- SQL (Proficient)