AI Engineer
Tasks
- Build machine learning models
- Conduct post-deployment evaluations
- Deploy AI models into production
- Design AI solutions to automate processes
- Develop and integrate generative AI tools
- Enhance personalization with AI
- Ensure AI initiatives comply with AI governance framework
- Gather requirements and define AI technical specifications
- Identify AI opportunities for business value
- Implement testing version control and continuous integration for AI models
- Lead AI lifecycle management
- Monitor AI models for bias and unethical outcomes
- Monitor model performance and retrain models
- Support data privacy and security best practices
Perks/Benefits
- Discounts from local vendors
- Fitness allowance
- Flexible national holidays
- Food allowance
- Gourmet lunches and healthy snacks
- Gourmet office lunches
- Mental well-being services
- Private health insurance
- Social events
- Training courses
- Wellness incentives
- Work from anywhere
Skills/Tech-stack
AI Governance | AI Platform | AI Security | AI ethics | AI model | AI model retraining | AI monitoring | AWS SageMaker | Azure AI | Continuous integration | Cortex AI | Data Privacy | Decision Trees | Deep learning | GDPR | Generative AI | Google AI | Google AI Platform | K-Means | K-means Clustering | Language Processing | Logistic Regression | MLOps | Machine Learning | Make | Model retraining | N8n | NLP | Natural Language | Natural Language Processing | Naïve Bayes | Neural Networks | Python | R | Random Forests | Regression | SQL | Snowflake Cortex | Snowflake Cortex AI | Supervised Learning | Support Vector Machines | Transformers | Unsupervised Learning | Vector machines | Version control
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Engineer | Engineer
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