Senior MLOps Engineer
Tasks
- Adopt GCP AI best practices across the company
- Advise teams on ML and AI architecture and tooling
- Build and maintain LLMOps infrastructure on GCP
- Build and maintain MLOps infrastructure on GCP
- Collaborate with data engineering and DevOps teams on CI CD
- Deploy models to production
- Design reliable scalable LLM solutions
- Design reliable scalable ML solutions
- Develop machine learning pipelines
- Enable models from experimentation to production
- Ensure reproducibility observability and maintainability
- Monitor model performance
Perks/Benefits
- Health insurance
- Language Courses Covered by Company
- Meal vouchers
- Mental health support
- Parental plan
- Remote work policy
- Subsidized gym membership
- Transportation cost coverage
- Vacation policy
Skills/Tech-stack
CI/CD | Cloud platform | Data Engineering | DevOps | Docker | GKE | GenAI | Google Cloud | Google Cloud Platform | Kubernetes | LLMOps | Language Models | Large Language Models | MLOps | Machine Learning | Machine Learning Pipelines | Model Deployment | Model Monitoring | Observability | PyTorch | Python | Quantum Computing | Reproducibility | Scikit-learn | TensorFlow | Vertex AI
Education
N/A
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