CT_NITRO Experimental AI Engineer
Tasks
- Automate data science infrastructure
- Build data models
- Deploy generative AI models
- Design generative AI models
- Develop large language models
- Develop machine learning algorithms
- Ensure scalability
- Identify storage requirements
- Implement data cleansing
- Integrate AI insights into products
- Manage data science lifecycle
- Migrate data between systems
- Optimize model performance
- Perform data acquisition
- Perform data preprocessing
- Perform peer review of models
- Recommend workflow improvements
- Review data quality
- Stay current with AI trends
- Validate machine learning models
Perks/Benefits
- 401k plan
- Flexible vacation policy
- Hybrid work model
- Medical and dental coverage
- Paid Holidays
- Paid time off
- Pension plan
Skills/Tech-stack
AWS | Azure | Batch Processing | Big Data | Cloud Computing | Containerization | Data Modeling | Data Visualization | Data Wrangling | Databricks | Distributed Computing | Docker | Document Database | Fine Tuning | GCP | GPU Computing | Generative AI | Git | Hadoop | Keras | Language Models | Language Processing | Large Language Models | MLlib | MXNet | Machine Learning | Natural Language | Natural Language Processing | Prompt engineering | PyTorch | Python | SQL | Scikit-learn | Spark | Supervised Learning | TensorFlow | Unsupervised Learning | Vector Database
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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