Machine Learning Engineer, Operations Technology
Tasks
- Automate operations and monitoring
- Build CI/CD pipelines
- Build production grade AI agent evaluations
- Deploy and maintain ML applications
- Design production machine learning systems
- Detect data drift
- Develop agentic generative AI system
- Generate images
- Implement model serving
- Improve data quality
- Integrate AI systems with content pipeline
- Measure quality reliability performance
- Monitor models
- Orchestrate LLM workflows
- Translate business needs into AI products
Perks/Benefits
- Career growth and development
- Fitness membership discount
- Flexible-hybrid work
- Generous vacation
- Health and dental benefits
- Health spending account
- Hybrid office days
- Learning Support
- Paid time off
- Parental leave top-up
- Remote work flexibility
- Unlimited Headspace access
Skills/Tech-stack
Agentic architecture | CI/CD | Data Drift | Data Drift Detection | Data Quality | Databricks | Drift Detection | Feature Engineering | Generative AI | Image Generation | Kubernetes | LLM orchestration | Language Models | Large Language Models | MLflow | Machine Learning | Model Monitoring | Model Serving | Prefect | Prompt engineering | PySpark | Python | SQL | Test-Driven | Test-Driven Development | Workflow Orchestration
Education
N/A
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