AI Engineering Manager
Tasks
- Architect AI/ML systems
- Architect GenAI systems
- Build NLP solutions
- Build computer vision solutions
- Build predictive analytics models
- Build reusable AI frameworks and tooling
- Define AI product vision
- Deploy ML models to production
- Design multi-agent orchestration
- Develop AI roadmaps
- Ensure fairness compliance
- Ensure model explainability
- Ensure responsible AI governance
- Establish model drift monitoring
- Establish performance monitoring
- Establish success metrics
- Identify AI opportunities
- Implement LLMOps for LLMs
- Implement MLOps for ML
- Implement RAG systems
- Implement automated retraining
- Implement model evaluation pipelines
- Implement model monitoring
- Implement prompt engineering
- Lead and mentor AI engineers and data scientists
- Lead cross-functional AI programs
- Perform model fine-tuning
- Promote knowledge sharing communities of practice
- Set up CI CD for ML
Perks/Benefits
- N/A
Skills/Tech-stack
API deployments | Automated retraining | BigQuery | CI/CD | Cloud Storage | Computer Vision | Dataflow | Docker | Documentation | Ensemble learning | Explainability | Fairness | Fine Tuning | Generative AI | Git | Keras | LLM | LLMOps | MLOps | Machine Learning | Model Evaluation | Model Monitoring | Model versioning | Modular Design | NLP | Neural Networks | Observability | Predictive Analytics | Prompt engineering | PyTorch | Python | RAG | Regression | Retrieval-Augmented Generation | Simulation optimization | TensorFlow | Testing | Vertex AI
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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