Pankaj Verma

Software Engineer

Bengaluru, Karnataka, India3 yrs 11 mos experience
Highly StableAI Enabled

Key Highlights

  • Expert in developing AI-driven solutions.
  • Proven track record in optimizing data pipelines.
  • Strong background in backend services and mapping technologies.
Stackforce AI infers this person is a Backend-focused Software Engineer with expertise in AI and data-driven solutions.

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Skills

Core Skills

GenaiPython (programming Language)Java

Other Skills

AirflowScalaPlay FrameworkPySparkBlender3D3D RenderingJavaScriptGo (Programming Language)DockerApache KafkaProgrammingC (Programming Language)C++Core Java

Experience

3 yrs 11 mos
Total Experience
3 yrs 7 mos
Average Tenure
6 mos
Current Experience

Publicis sapient

Senior Software Engineer

Dec 2025Present · 6 mos · Bengaluru, Karnataka, India

Ola

2 roles

SDE-2

Aug 2024Feb 2026 · 1 yr 6 mos · Bengaluru, Karnataka, India

  • Built an MCP server for Ola Maps. Released for public as python package and on Docker hub. Hosted enhanced version remotely as well for Krutrim AI assistant to use.
  • Built AI assistant chat bot for Ola Maps platform.
  • Built Geoquery service utilising Ola Maps capabilities specific to Client use cases.
  • Built 3D maps capabilities.
  • Led Infrastructure migration of Maps Tiles services from AWS to Krutrim Cloud.
  • Enhanced and optimized existing data automation pipelines.
GenAIPython (Programming Language)

SDE-1

Jul 2022Aug 2024 · 2 yrs 1 mo · Bengaluru, Karnataka, India

  • Developed a high-performance compression filter for Location Based Services, reducing in-house API response sizes by ~52% using Java, Scala, and Play Framework.
  • Engineered routing logic for the Reverse Geocoding API, dynamically directing traffic between in-house services and external providers based on configurable conditions; scaled reliably to ~2 million RPM with low latency.
  • Enhanced the Marauder routing system to support speed segment file inputs for OSRM, automating hourly and daily updates and improving route accuracy by ~10%.
  • Improved ETA and routing accuracy by ~30% using tree-based machine learning models.
  • Reduced incremental map update latency from ~3 days to ~1 hour by implementing ML-based way-ID popularity prediction pipelines using PySpark and Python.
  • Developed and maintained backend services and data pipelines supporting location, routing, and mapping use cases at scale.
  • Worked extensively with Python and Airflow to build and optimize batch and streaming workflows for map and routing data.
  • Assisted in designing scalable APIs and internal services with a focus on reliability, performance, and maintainability.
Python (Programming Language)Airflow

Education

Indian Institute of Technology, Madras

M. Tech. — Computer Science and Engineering

Jan 2020Jan 2022

Rajasthan Technical University

B.Tech — Computer Science

Jan 2016Jan 2020

Kendriya Vidyalaya

Jan 2013Jan 2015

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