Key skills
CloudDockerGoogle Cloud PlatformKubernetesPythonPyTorchScikit-LearnTensorflowAIMachine LearningMLTensorFlowscikit-learnLangChainLangGraphGCPGoogle CloudRemote Work
About this role
Role Overview
- Design, develop, and deploy machine learning models and solutions
- Collaborate on building and maintaining scalable data and feature pipeline infrastructure
- Develop and implement strategies for model monitoring and observability
- Optimize ML model inference performance
- Ensure overall reliability and scalability of ML models
- Troubleshoot complex issues affecting ML models and production AI systems
- Ensure AI/ML models meet data governance 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 and observability best practices
- Experience in Python and ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn)
- Familiarity with AI orchestration concepts (LangGraph or LangChain is a bonus)
- Bonus experience in gaming, real-time fraud detection, or AI personalization systems
Tech Stack
- Cloud
- Docker
- Google Cloud Platform
- Kubernetes
- Python
- PyTorch
- Scikit-Learn
- Tensorflow
Benefits
- Health insurance
- Flexible work arrangements
- Professional development
- Remote work options