Key skills
CloudDockerGoogle Cloud PlatformKubernetesPythonAIMachine LearningMLLangChainLangGraphGCPGoogle CloudRemote Work
About this role
Role Overview
- Design, develop, and deploy machine learning models
- Collaborate on building and maintaining scalable data and feature pipeline infrastructure
- Develop and implement robust strategies for model monitoring and observability
- Optimize ML model inference performance
- Ensure the reliability and performance of the ML models and data infrastructure platform
- Troubleshoot and resolve complex issues impacting ML models
- Ensure AI/ML models and workflows meet data governance, security, and compliance requirements
Requirements
- 1+ years of experience as an ML Engineer
- Strong experience in Google Cloud Platform (GCP)
- Solid grasp of containerization (Docker, Kubernetes)
- Experience building and deploying scalable data pipelines
- Understanding of model monitoring, logging, and observability best practices
- Experience in Python and ML frameworks
- Familiarity with AI orchestration concepts using tools like LangGraph or LangChain is a bonus
- Bonus experience includes working in gaming, real-time fraud detection, or AI personalization systems
Tech Stack
- Cloud
- Docker
- Google Cloud Platform
- Kubernetes
- Python
Benefits
- Remote work flexibility
- Professional development opportunities