Full-Time ML Engineer / DevOps AWS AI Team

• ML Model Deployment: Develop, deploy, and manage production-grade AI and machine learning pipelines, focusing particularly on Computer Vision models.
• Infrastructure Automation/ DevOps: Build and maintain scalable, automated infrastructure and CI/CD pipelines to streamline model development, testing, deployment, and monitoring.
• Monitoring & Optimization: Implement and enhance monitoring tools to track model performance, detect drift, and optimize system efficiency and reliability.
• Collaboration & Support: Work closely with AI engineers, data scientists, and software engineers to ensure effective integration and deployment of machine learning solutions.
• Best Practices: Establish and enforce best practices in ML Ops, including version control, reproducibility, security, and performance optimization.

• 5+ years of experience in ML Ops and DevOps, or similar roles, specifically supporting AI/ML initiatives.
• Strong experience with machine learning frameworks such as PyTorch or TensorFlow.
• Expertise in containerization technologies (Docker, Kubernetes) and AWS cloud infrastructure.
• Proven track record deploying and scaling ML models into production environments.
• Proficiency in automation tools and CI/CD pipelines (e.g., GitLab CI, Bitbucket, GitHub Actions).
• Experience with monitoring tools and logging frameworks for ML systems (e.g., Prometheus, Grafana, ELK stack).
• Excellent communication skills in English.

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