Adhri P.

Key Skills

Software

CrowdSource

Top Subject Matter

ATIP (Access to Information and Privacy) document automation and LLM querying

MLOps and LLM application delivery (chatbots and RAG)

Predictive analytics and operational data pipelines for government programs

Top Data Types

Document

Video

Text

Top Task Types

Question Answering

Computer Programming/Coding

Text Generation

Text Summarization

Freelancer Overview

AI Lead & Software Architect, Enterprise Solutions Directorate, Transport Canada (TC). Brings 20+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Internal, Proprietary Tooling, and Other. Education includes Master of Science, Lakehead University (2021) and Bachelor of Science, Cornell University (2006). AI-training focus includes data types such as Document and labeling workflows including Question Answering, Evaluation, and Rating.

Labeling Experience

AI Lead & Software Architect, Enterprise Solutions Directorate, Transport Canada (TC)

DocumentQuestion Answering

Developed an AI component for an ATIP modernization system that enables users to intelligently query documents. Used Azure OpenAI API to support document understanding tasks such as duplicate removal and auto versioning. Worked as AI lead and supervised related system development and DevOps to deploy the capability for federal users. • Translated user requirements into architecture and database design for document processing • Built LLM-based querying over user documents • Implemented preprocessing/logic to remove duplicates and manage document versions • Coordinated interoperability with other government systems (e.g., SharePoint, Azure Blob Storage)

2025 - Present

Programmer/Analyst, Enterprise Business Intelligence & Data Analytics (eBIDA), Transport Canada

OtherDocumentQuestion Answering

Joined an MLOps/LLM team to deliver LLM-based solutions for teams across Transport Canada. Set up Databricks infrastructure to support development and operationalization of LLM projects, ranging from chatbots to RAG systems. Authored documentation for monitoring and MLOps environment components to ensure reliable usage of deployed models. • Configured Databricks compute clusters, data catalog, and permissions for developers • Implemented multiple LLM deliverables including chatbot and RAG-style systems • Produced monitoring scripts, dashboard assets, and operational documentation • Supported model delivery with MLOps workflows and usage tracking

2024 - 2025

Data Scientist (and acting manager), Chief Data Office, Transport Canada (TC)

OtherDocument

Developed analytics solutions and operational dashboards that supported data-driven decision-making across Transport Canada programs. Built and implemented predictive models (e.g., traffic collision forecasting) and established data pipelines feeding visualization tools. Conducted engineering work to overcome technical challenges and improve interoperability between previously incompatible systems, including transitioning teams to DevOps for efficient project management. • Created operational dashboards for Grants & Contributions and published mandated datasets via Open Government • Built forecasting models for road safety using structured data pipelines • Introduced advanced predictive analytics and addressed interoperability between systems • Trained/coached junior developers and supervised co-op students to maintain delivery processes

2019 - 2024

Annotating CRA Data

TextText Summarization

As part of my master's research into text summarization, I received an internal dataset from CRA, with original and summarized content. I went through the 5000 entry data set to manually annotate the quality of summarization presented

2019 - 2020

Education

Work History