Engineering Manager – AI Platforms
Tasks
- Apply responsible AI guardrails
- Conduct performance reviews and define career paths
- Conduct technical architecture reviews
- Drive MLOps pipelines
- Ensure reliability and observability for deployed models
- Ensure security and compliance for AI platforms
- Evolve experimental models into enterprise platforms
- Implement GDPR and SOC2 controls
- Implement model monitoring and drift detection
- Manage software engineers and ML and GenAI engineers
- Mitigate bias and ensure data privacy
- Oversee scalable machine learning workflows
- Own AI platform roadmap
- Provide architectural guidance for AI integrations
- Transition research notebooks to production code
- Translate platform capabilities into executive insights
Perks/Benefits
- Collaborative team environment
- Global consulting experience
- Leadership development programs
- Training sessions
Skills/Tech-stack
AWS Bedrock | Agentic Workflows | Agile | Amazon SageMaker | Azure AI | CI/CD | Capacity Planning | Cloud Native | Data Analysis | Data Privacy | Deep learning | Distributed Systems | Docker | Drift Detection | Exploratory Data Analysis | Feature Engineering | GDPR | GenAIOps | Google Vertex | Google Vertex AI | Kubernetes | Language Models | Language Processing | Large Language Models | MLOps | Machine Learning | Model Monitoring | Model Validation | Natural Language | Natural Language Processing | Retrieval-Augmented Generation | SOC2 | Scrum | Vector Databases | Vertex AI
Education
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