Data Scientist
Tasks
- Apply parameter efficient fine tuning
- Apply prompt tuning
- Apply supervised fine tuning
- Apply transfer learning
- Build machine learning training pipelines
- Deploy models to production
- Document tools and technical decisions
- Evaluate models and improve scalability
- Monitor training stability and accuracy
- Optimize model performance
- Prepare and process large real world datasets
- Select model and training approaches
- Train and fine-tune large language models
- Troubleshoot training and GPU performance issues
- Work with structured unstructured time series and streaming data
Perks/Benefits
- N/A
Skills/Tech-stack
CUDA | Data Governance | Data Privacy | Deep learning | Distributed Training | Docker | Efficient Fine Tuning | Fine Tuning | GPUs | Hugging Face | Hugging Face Transformers | Kubernetes | Language Models | Large Language Models | LoRA | MLOps | MLflow | Machine Learning | Model Compression | Model Evaluation | Model Optimization | PEFT | Parameter efficient fine-tuning | Prompt Tuning | PyTorch | Python | QLoRA | Quantization | Supervised Fine Tuning | Supervised Learning | TensorFlow | Tokenization | Transfer Learning
Education
N/A
Roles
AI | AI Engineer | Data Scientist | Engineer | Learning Engineer | Machine Learning Engineer | Scientist | Senior Data Scientist
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