Data Scientist (Generative AI)
Tasks
- Build and optimize neural network architectures
- Create few shot examples
- Deploy models to production
- Design machine learning models
- Design prompts and system instructions
- Evaluate generative model performance
- Fine-tune foundational models
- Implement retrieval-augmented generation
- Integrate models into RAG pipelines
- Measure model metrics
- Prepare and label datasets
- Run experiments and benchmarks
- Support Agile development lifecycle
- Synthesize datasets
- Train generative models
- Update AI research trends
Perks/Benefits
- N/A
Skills/Tech-stack
APIs | AWS Bedrock | AWS Kendra | AWS SageMaker | Adversarial Networks | Amazon Web Services | ArcGIS | Attention Mechanisms | Azure | Azure Cognitive | Azure Cognitive Search | Azure OpenAI | BLEU | Cloud platform | Cognitive Search | D3.js | Data Generation | Data Governance | Data labeling | DevSecOps | Docker | Elasticsearch | Embeddings | Fine Tuning | Generative Adversarial Networks | Git | Google Cloud | Google Cloud Platform | Hugging Face | Hugging Face Transformers | Human evaluation | Instruction Tuning | JAX | Jupyter | Keras | Language Models | Language Processing | Large Language Models | MLOps | Machine Learning | Model Evaluation | Model Fine-tuning | Natural Language | Natural Language Processing | Network Architecture | Neural Network | Neural Network Architecture | NumPy | Pandas | Perplexity | Power BI | Prompt engineering | PyTorch | Python | RAG | ROUGE | Reinforcement Learning | Retrieval-Augmented Generation | SciPy | Scikit-learn | Supervised Learning | Synthetic Data Generation | Synthetic data | Tableau | TensorFlow | Tokenization | Transformers | Variational Autoencoders | Web Services
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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