Sr MLOps and Automation Engineer
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Locations: Cork, Ireland
Time Type: Full Time
Posted On: Posted Yesterday
Job Requisition ID: R11371
It's fun to work in a company where people truly BELIEVE in what they're doing!
We're committed to bringing passion and customer focus to the business.
Corporate Overview
Proofpoint is a leading cybersecurity company protecting organizations’ greatest assets and biggest risks: vulnerabilities in people. With an integrated suite of cloud-based solutions, Proofpoint helps companies around the world stop targeted threats, safeguard their data, and make their users more resilient against cyber-attacks.
Role Overview
As an ML Ops and Automation Engineer, you will be at the forefront of bridging the gap between machine learning (ML) development and production deployment, ensuring smooth and efficient operations of ML systems. Your primary focus will be on designing, implementing, and maintaining automated pipelines for model training, deployment, monitoring, and scaling.
Key Responsibilities
1. Design and Implement ML Pipelines: Develop end-to-end automation pipelines for ML model training, validation, deployment, and monitoring, integrating with CI/CD systems and version control tools.
2. Infrastructure Orchestration: Architect and manage scalable, reliable infrastructure for ML workloads, leveraging cloud services (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).
3. Model Versioning and Experiment Tracking: Establish frameworks for versioning ML models and tracking experiment results, enabling reproducibility and collaboration among data scientists and ML engineers.
4. Continuous Integration/Continuous Deployment (CI/CD): Implement CI/CD pipelines for automated testing, deployment, and rollback of ML models, ensuring rapid iteration and deployment cycles.
5. Monitoring and Alerting: Set up robust monitoring and alerting systems to track the performance, health, and drift of deployed ML models in real-time, proactively identifying and addressing issues.
6. Optimization and Scaling: Optimize ML workflows for efficiency and cost-effectiveness, and scale infrastructure to accommodate growing data volumes and user loads.
7. Security and Compliance: Implement best practices for data security, privacy, and compliance (e.g., GDPR, HIPAA), and ensure adherence to regulatory requirements in ML workflows and deployments.
What you bring to the team:
1. Bachelor's or Master's degree in Computer Science, Engineering, or related field.
2. Strong programming skills in languages such as Python, Node.js, or Scala.
3. Experience with ML frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn).
4. Proficiency in cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).
5. Familiarity with CI/CD tools (e.g., Jenkins, GitLab CI/CD) and version control systems (e.g., Git).
6. Solid understanding of DevOps principles and practices.
7. Excellent problem-solving and communication skills, with a collaborative mindset.
8. Experience with big data technologies (e.g., Apache Spark, Hadoop).
9. Knowledge of software engineering best practices and agile methodologies.
10. Understanding of machine learning concepts and techniques.
11. Certification in cloud computing or DevOps.
Why Proofpoint
Protecting people is at the heart of our award-winning lineup of cybersecurity solutions, and the people who work here are the key to our success. We are an inclusive, diverse, multinational company that believes in culture fit, but more importantly ‘culture-add’, and we strongly encourage people from all walks of life to apply.
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