NLP Full stack data scientist

Company:
Location: Chennai, Tamil Nadu

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Job Description & Qualifications

  • Design NLP applications/products by following robust coding practices
  • Explore SoTA models/techniques so that they can be applied for automotive industry usecases
  • Conduct ML experiments to train/infer models; if need be, build models that abide by memory & latency restrictions
  • Deploy REST APIs or a minimalistic UI for NLP applications using Docker and Kubernetes tools
  • Showcase NLP applications in the best way possible to users through web frameworks (Dash, Plotly, Streamlit, etc.,)

Auto req ID

47618BR

Entity/Organization

FIPL - Ford India Pvt Ltd

Area of professional exposure (technical skills)

NLP Skills:
  • Knowledge in fundamental text data processing (like use of regex, token/word analysis, spelling correction/noise reduction in text, segmenting noisy unfamiliar sentences/phrases at right places, deriving insights from clustering, etc.,)
  • Have implemented in real-world BERT/or other transformer fine-tuned models (Seq classification, NER or QA) from data preparation, model creation and inference till deployment

ML/DL Skills:
  • High familiarity in the use of DL theory/practices in NLP applications
  • Comfort level to code in Tensorflow and/or Pytorch
  • Comfort level to code in Scikit-learn, Numpy and Pandas
  • Comfort level to use two/more of open source NLP modules like SpaCy, HuggingFace, TorchText, fastai.text, farm-haystack, and others

Python Project Management Skills
  • Familiarity in the use of Docker tools, pipenv/conda/poetry env
  • Comfort level in following Python project management best practices (use of setup.py, logging, pytests, relative module imports,sphinx docs,etc.,)
  • Familiarity in use of Github (clone, fetch, pull/push,raising issues and PR, etc.,)

Deployment Skills:
  • Use of Dockers (experience in experimental docker features, docker-compose, etc.,)
  • Kubernetes or any other containerization tool with experience in Helm, Argoworkflow, etc.,

UI:
  • Good UI skills to visualize and build better applications using Dash, Streamlit, Django, etc.,
  • Deeper understanding of javascript, css, html, etc., is a plus

Miscellaneous Skills:
Data Engineering:
  • Skillsets to perform distributed computing (specifically parallelism and scalability in Data Processing, Modeling and Inferencing through Spark, Dask, RapidsAI or RapidscuDF)
  • Ability to build python-based APIs (e.g.: use of FastAPIs/ Flask/ Django for APIs)
  • Experience in Elastic Search and Apache Solr is a plus
Cloud Computing:
  • Skillset to leverage cloud platform for Data Engineering, Big Data and ML needs

Education Qualifications

B.E., B.Tech., MCA

No. of years of experience

5 to 8 years

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