AI Engineering Manager
Tasks
- Apply machine learning algorithms
- Build AI with TensorFlow PyTorch Keras
- Build engineering standards
- Build predictive models
- Define AI product vision
- Deliver AI products
- Deploy models with Docker and APIs
- Design RAG systems
- Develop AI talent
- Develop deep learning neural networks
- Drive AI research and innovation
- Encourage experimentation
- Ensure scalable deployment
- Ensure software engineering best practices
- Establish governance for Responsible AI
- Foster community sharing
- Identify AI opportunities
- Implement MLOps practices
- Implement NLP and computer vision solutions
- Implement ethical AI principles
- Lead AI strategy
- Lead AI teams
- Lead multi-agent systems
- Manage cloud AI services
- Monitor system performance
- Oversee end-to-end AI systems
- Partner with business leaders
- Review AI architecture
- Work with LLMs and foundation models
Perks/Benefits
- N/A
Skills/Tech-stack
AI Governance | APIs | Agent systems | BigQuery | Cloud Storage | Computer Vision | Dataflow | Deep learning | Docker | Ensemble Methods | Ethical AI | Evaluation Pipelines | Fairness | Fine Tuning | GCP | Git | Image Processing | Keras | LLMOps | LLMs | ML algorithms | MLOps | Machine Learning | Model Explainability | Multi-Agent | Multi-Agent Systems | NLP | NLP Techniques | Neural Networks | PyTorch | Python | RAG Systems | Regression | Software Engineering | TensorFlow | Vertex AI
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
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