About the role
- Architect and design a Python package to help users create scalable pipelines, to go from ‘raw data’ to a trained AI model; including data filtering, data cleaning, data visualization, synthetic data creation, and integration into ML training (incl RL)
- Work with large datasets to develop both generic models as well as fine-tuned AI models, especially LLMs, using the package
- Continually improve the package by incorporating state-of-the-art techniques and frameworks
Experence
- 10+ years experience in data engineering or similar roles, with strong knowledge of designing and implementing complex AI and ML solutions, as a Senior Data Scientist, Machine Learning Engineer, or AI Engineer
- Strong proficiency in building large-scale data processing pipelines with AI training, familiar with distributed workloads (e.g., multiprocessing, MPI, Ray, Dask, Spark)
- Experience developing end-to-end pipelines for model training; from handling structured and unstructured data sources to cleaning and creating synthetic data to actual training
- Experience with AI technologies across the training journey, intimate familiarity with using Pytorch/ Horovod/ TensorflowAbility to take extreme ownership over your work
- Excellent problem-solving and communication skills
- Active GitHub contributions are a big plus
- Built Data pipelines for ML Training (Must, Ideally: Ray)
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