Data Scientist (Generative AI)
Tasks
- Build Retrieval Augmented Generation systems
- Collaborate with engineers to transition models to production
- Define benchmarks and evaluation metrics
- Deploy models to production
- Design and train machine learning models
- Design prompt and few shot strategies
- Develop generative models
- Evaluate foundational model performance
- Fine tune models with supervised tuning reinforcement tuning instruction tuning
- Prepare and label datasets
- Run experiments to measure hallucination factuality coherence safety
- Support agile software development lifecycle
Perks/Benefits
- N/A
Skills/Tech-stack
APIs | AWS Bedrock | AWS Kendra | AWS SageMaker | Adversarial Networks | Attention Mechanisms | Azure Cognitive | Azure Cognitive Search | Azure OpenAI | BLEU | Cloud Computing | Cognitive Search | Data Generation | Data Governance | Data labeling | DevSecOps | Docker | Elasticsearch | Embeddings | Fine Tuning | Generative Adversarial Networks | Git | Hugging Face | Hugging Face Transformers | Instruction Tuning | JAX | Jupyter | Keras | Language Processing | MLOps | Machine Learning | Model Evaluation | Natural Language | Natural Language Processing | NumPy | Pandas | Perplexity | Power BI | Prompt engineering | PyTorch | Python | ROUGE | Reinforcement Learning | Retrieval-Augmented Generation | SciPy | Scikit-learn | Supervised Fine Tuning | Supervised Learning | Synthetic Data Generation | Synthetic data | Tableau | TensorFlow | Tokenization | Transformer | Variational Autoencoders
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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