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Python Developer with GenAI

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Onsite

Python Developer with GenAI

Grid Dynamics

Python Developer with GenAI

Skills

SQL QueriesPythonNumPypandasPyTorchTensorFlowData AnalysisMachine LearningAI

1 month ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

26 September 2026

What they need


Grid Dynamics (Nasdaq:GDYN) is a digital-native technology services provider that accelerates growth and bolsters competitive advantage for Fortune 1000 companies. Grid Dynamics provides digital transformation consulting and implementation services in omnichannel customer experience, big data analytics, search, artificial intelligence, cloud migration, and application modernization. Grid Dynamics achieves high speed-to-market, quality, and efficiency by using technology accelerators, an agile delivery culture, and its pool of global engineering talent. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the US, UK, Netherlands, Mexico, India, Central and Eastern Europe.

To learn more about Grid Dynamics, please visit www.griddynamics.com . Follow us on Facebook , Twitter , and LinkedIn .

Job Description:

Key Responsibilities

Predictive Analytics & Forecasting

  • Design, develop, and deploy predictive models to support business planning, forecasting, scenario modelling, and performance optimization.
  • Develop machine learning solutions using structured, semi-structured, and unstructured enterprise datasets.
  • Create statistical models that improve forecasting accuracy and support strategic decision making.
  • Build explainable models and communicate key drivers, assumptions, risks, and confidence intervals.
  • 3+ years of experience in Python Development with GenAI.

Technical Skills

Strong hands-on experience with:

  • Python
  • Pandas
  • NumPy
  • Scikit-Learn
  • XGBoost
  • RandomForest
  • LightGBM
  • PyTorch and/or TensorFlow
  • SQL

AI & GenAI Skills

Hands-on experience with:

  • Large Language Models (LLMs)
  • RAG architectures
  • Prompt engineering
  • Vector search
  • Embedding models
  • Agentic AI workflows
  • LangChain
  • LangGraph
  • LangSmith
  • AutoGen or equivalent frameworks

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