Software Developer – Intermediate

Job Overview

The Government of Ontario is undertaking a major Data and AI transformation initiative focused on developing the Ontario Data Platform (ODP).

The Ontario Data Platform is an enterprise technology ecosystem designed to support Data and AI solutions, including data ingestion, storage, processing, visualization, governance, quality, and marketplace capabilities.

The selected candidate will support various Data Science and AI/ML initiatives, assisting with model inference execution, pipeline evaluation, dataset preparation, and performance monitoring.

Key Responsibilities

Inference Execution and Monitoring

• Execute batch inference jobs using Databricks and other environments.
  

• Monitor inference processes and troubleshoot execution issues.
  

• Log results and escalate model anomalies when required.
  

Pipeline and Model Evaluation

• Assist in running DSPy pipelines and loading custom models and configurations.
  

• Support model evaluation runs using internal performance metrics.
  

• Track, analyze, and summarize performance metrics for inference experiments.
  

Data Preparation and Experimentation

• Prepare and clean legal text datasets for inference and evaluation.
  

• Annotate model outputs to support error analysis and benchmarking.
  

• Maintain reproducible scripts and notebooks for inference experiments.
  

Must-Have Skills and Qualifications

• Educational background in Computer Science, Data Science, Artificial Intelligence, or Machine Learning. Students and recent graduates are welcome.
  

• Familiarity with Python programming.
  

• Experience or exposure to Python libraries such as:
  

  • Pandas
    

  • Scikit-learn
    

  • PyTorch
    

• Exposure to Large Language Model (LLM) frameworks such as:
  

  • DSPy
    

  • LangChain
    

  • Hugging Face
    

  • Equivalent LLM frameworks
    

• Familiarity with Databricks, MLflow, or other cloud-based Machine Learning environments.
  

• Strong attention to detail and organizational skills.
  

• Ability to track experiments, document results, and maintain reproducible workflows.
  

Requirements

Ideal Candidate Profile

• Computer Science, Data Science, or AI/ML student or recent graduate.
  

• Hands-on Python knowledge.
  

• Basic understanding of Machine Learning and LLM concepts.
  

• Exposure to DSPy, LangChain, Hugging Face, or similar frameworks.
  

• Familiarity with Databricks or MLflow.
  

• Strong analytical, documentation, and problem-solving skills.