Required Skills

Databricks ADLS PostgresDB event hubs

Work Authorization

  • US Citizen

  • Green Card

  • EAD (OPT/CPT/GC/H4)

  • H1B Work Permit

Preferred Employment

  • Corp-Corp

  • W2-Permanent

  • W2-Contract

  • Contract to Hire

Employment Type

  • Consulting/Contract

education qualification

  • UG :- - Not Required

  • PG :- - Not Required

Other Information

  • No of position :- ( 1 )

  • Post :- 5th Mar 2024

JOB DETAIL

  • Sr. Data Platform Engineer (REMOTE) needed --- Data Platform Engineering,  Master's degree, Data Platform, AZURE Infrastructure, importantly Data bricks, ADLS, PostgresDB, Event Hubs, AKS, Data bricks Admin, Databricks Certified, latest releases (Unity Catalog), Python. Python + SQL, MLOps, CI/CD GitHub, GitHub Actions, No. of Models / Pipelines, Large Language Model (LLM) Agents (for 3 use cases, IGS, HBT, PMT), Pipeline to create / improve evaluation framework for LLMs, Test Model Performance / Accuracy, Perform prompt engineering, Create the pipelines as reusable components, Create a pipeline to fine-tune an open-source model 
  • Qualified candidates will have 6+ years of Data Platform Engineer experience and a college degree. Master's degree + 6 + years of experience. 
  • 6+ years of hands-on skills as a Data Platform Engineer.
  • AZURE Infrastructure experience – importantly Databricks, ADLS, PostgresDB, event hubs, and AKS
  • Databricks Admin – Certified candidates preferred – ideally in the latest releases that include the Unity Catalog.
  • Able to code in Python. Python + SQL.
  • High-level understanding of MLOps.
  • CI/CD GitHub, GitHub actions etc.
  • Excellent communication skills both verbal and written are required. 
  • No. of models/pipelines - Large Language Model (LLM) Agents (for 3 use cases, IGS, HBT, PMT) with a set of tools developed for the individual use cases.
  • Pipeline to create and improve the evaluation framework for the Large Language Model (LLMs)  to test model performance and accuracy.
  • Perform prompt engineering for the existing toolset to fit the use case and evaluate using the above framework.
  • Create the pipelines as reusable components for additional use cases. the pipeline includes the tools, agents, base prompts, evaluation framework, etc
  • Create a pipeline to fine-tune an open-source model based on the feedback received from the beta releases of the app.

Company Information