Senior Health Data Scientist leading complex data extraction and modeling for healthcare solutions at Inovalon. Collaborating with multidisciplinary teams to deliver data - driven insights.
About the role
- Data Science/Gen AI Specialist working with NLP and LLM applications for automotive solutions. Responsibilities include design, deployment, and showcasing AI applications.
Responsibilities
- Design NLP/LLM/GenAI 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/LLM/GenAI applications in the best way possible to users through web frameworks (Dash, Plotly, Streamlit, etc.)
- Converge multibots into super apps using LLMs with multimodalities
- Build modular AI/ML products that could be consumed at scale.
Requirements
- Bachelor’s or master’s degree in computer science, Engineering, Maths or Science
- Strong communication skills and do excellent teamwork through Git/slack/email/call with multiple team members across geographies.
- Experience in LLM models like PaLM, GPT4, Mistral (open-source models)
- Work through the complete lifecycle of Gen AI model development, from training and testing to deployment and performance monitoring.
- Developing and maintaining AI pipelines with multimodalities like text, image, audio etc.
- Experience in developing Image generation/translation tools using any of the latent diffusion models like stable diffusion, Instruct pix2pix.
- High familiarity in the use of DL theory/practices in NLP applications
- Comfort level to code in Huggingface, LangChain, Chainlit, Tensorflow and/or Pytorch, Scikit-learn, Numpy and Pandas
- Knowledge in fundamental text data processing (like use of regex, token/word analysis, spelling correction/noise reduction in text, etc.)
- Familiarity in the use of Docker tools, pipenv/conda/poetry env
- Good working knowledge on other open-source packages to benchmark and derive summary.
- Experience in using GPU/CPU of cloud and on-prem infrastructures.
- Familiarity with orchestration tools such as airflow, Kubeflow
- Good UI skills to visualize and build better applications using Gradio, Dash, Streamlit, React, Django, etc.
- Skillsets to perform distributed computing through Spark, Dask, RapidsAI or RapidscuDF
- Experience in Elastic Search and Apache Solr is a plus, vector databases.
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