Data Scientist (Generative AI)
Tasks
- Deploy generative models to production
- Design and optimize prompts for LLMs
- Design and train generative machine learning models
- Design experiments for model behavior evaluation
- Evaluate foundational model performance
- Fine-tune generative models
- Integrate AI solutions with cross-functional teams
- Prepare datasets for training and RAG
- Support agile software development lifecycle
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | AWS Bedrock | AWS SageMaker | Adversarial Networks | Attention Mechanisms | Azure | Azure OpenAI | BLEU | Cloud platform | Data Generation | Data Governance | Data labeling | DevSecOps | Docker | Embeddings | Generative Adversarial Networks | Generative Models | Git | Google Cloud | Google Cloud Platform | Human evaluation | Instruction Tuning | JAX | Jupyter | Keras | Language Models | Language Processing | Large Language Models | MLOps | MLOps Model Training | Machine Learning | Model Training | Natural Language | Natural Language Processing | NumPy | Pandas | Perplexity | Prompt engineering | PyTorch | Python | RAG | REST APIs | ROUGE | Reinforcement Learning | Retrieval-Augmented Generation | SciPy | Scikit-learn | Supervised Learning | Synthetic Data Generation | Synthetic data | TensorFlow | Tokenization | Transformers | Variational Autoencoders
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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