Data Scientist

2 weeks ago

Santa Clara, United States Net2Source Inc. Full time

Data Scientist

Location - Santa Clara, CA (Hybrid)

Contract/ Full Time


This is data scientist role focused on transforming complex and large (100s of terabytes) multi-dimensional data e.g. tabular(relational) , unstructured data such as images, videos, audio files and other various file formats. The key responsibility is to be able to curate high quality training data for the large language model training.


Responsibilities:

  • Curate high-quality datasets and synthesize training data where needed to improve model capabilities.
  • Championing modelling , EDA, Transformation, Modernization and Curation of high-quality training data for GPT-4 and GPT-4 Vision
  • Providing data curation leadership on tabular, unstructured (images, video, logs files etc.) data
  • Creating data definitions and data lineages for effective LLM training for high accuracy
  • Helping build and test prompts to render high quality insights
  • Train and fine-tune language models using frameworks like PyTorch and TensorFlow
  • Rigorously test models to evaluate accuracy, bias, toxicity, and other attributes using statistical analysis
  • Monitor metrics and logs from LLMs in deployment to proactively identify any degraded performance or anomalies.
  • Diagnose root causes when models err or behave unexpectedly using techniques like saliency maps, heatmap visualizations and interactive debugging.
  • Improve model robustness by analyzing model behavior and identifying failure modes. Recommend data augmentation, training modifications etc.
  • Perform model surgery by carefully editing model weights and architectures to fix incorrect or unsafe behavior while maintaining performance.
  • Run A/B experiments to measure impact of model tweaks and fixes on performance, accuracy, toxicity, bias etc.
  • Continuously inspect models for signs of concept drift or staleness and recommend retraining cadence.
  • Document LLM version changes, experiments, and incident response postmortems.
  • Stay updated on the latest techniques from research and industry conferences for responsible and reliable deployment of LLMs.

Requirements:

  • 8+ years experience training, deploying and monitoring natural language models
  • Strong stats skills and large-scale data manipulation capabilities
  • Proficiency of Azure Machine Learning Studio and deploying models in Azure Cloud environments
  • Deep knowledge of Azure SQL and vector databases
  • Proficiency in Python, PyTorch, TensorFlow, NLP libraries and other ML tools
  • Knowledge of responsible AI principles around transparency, fairness and accountability
  • Monitor metrics and logs from LLMs in deployment to proactively identify any degraded performance or anomalies.
  • Diagnose root causes when models err or behave unexpectedly using techniques like saliency maps, heatmap visualizations and interactive debugging.
  • Improve model robustness by analyzing model behavior and identifying failure modes. Recommend data augmentation, training modifications etc.
  • Perform model surgery by carefully editing model weights and architectures to fix incorrect or unsafe behavior while maintaining performance.
  • Run A/B experiments to measure impact of model tweaks and fixes on performance, accuracy, toxicity, bias etc.
  • Continuously inspect models for signs of concept drift or staleness and recommend retraining cadence.
  • Document LLM version changes, experiments, and incident response postmortems.
  • Stay updated on the latest techniques from research and industry conferences for responsible and reliable deployment of LLMs.
  • Knowledge of Autogen, LangChain/Llama Index frameworks

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