Consultant Senior/Manager - ML/LLM Engineer
Tasks
- Benchmark MLOps solutions and recommend best fit
- Build ML and LLM pipelines with automation
- Define AI solution governance and development processes
- Deploy MLOps and LLMOps frameworks
- Design tools for model performance tracking drift data quality costs
- Develop GenAI use cases with pretrained models
- Implement ML monitoring and continuous maintenance
- Manage teams and coordinate stakeholders
- Pilot AI and generative AI projects end to end
- Train client teams on MLOps practices and tools
Perks/Benefits
Skills/Tech-stack
AWS SageMaker | Azure DevOps | CI/CD | DVC | Data Quality | Databricks | Dataiku | Generative AI | Google Cloud | Google Cloud Vertex | Google Cloud Vertex AI | Kedro | Kubeflow | Kubernetes | LLM | LLMOps | MLOps | MLflow | Machine Learning | Machine learning monitoring | Microsoft Azure | Model Drift | Monitoring | Vertex AI
Education
N/A
Roles
AI | AI Engineer | Engineer | LLM Engineer | ML Engineer
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