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Amyantek

RQ11580 – AI/ML Engineer (LLM, Python, Databricks) | Ontario Government | Onsite Toronto

Toronto, ON, Canada

Contract

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Job details

Job type: Contract
Apply by: Dec 9, 2026
Posting language: English
Posted: Nov 9, 2026

Original job description

Please send your resume at anila.dada@amyantek.com if you are interested in this approx. 04 months contract with Ontario Public Service (Ministry of Public and Business Service Delivery and Procurement) with a possibility of extension, If you are not interested, please feel free to pass it in your network for anyone looking for work.

Job Title: RQ11580 - Senior Software Developer

Working Status: On-Site

Location: 222 Jarvis Street

Start Date: 2026-09-10

End Date: 2027-03-31

Hours per day: 7.25

Description

The Government of Ontario is embarking on a large Data & AI transformation initiative. Core to the transformation is the enablement of the Ontario Data Platform (ODP), which is being developed as the enterprise technology ecosystem for everything Data & AI. ODP is a modern ecosystem of data solution consisting of data ingestion technologies, storage, processing and visualization as well as solutions related to data governance, quality, marketplace, etc. ODP will initially serve all internal government clusters, ministries and program areas, but also external agencies in the future. We are looking for a data scientist to support various initiatives related to the platform as well as the execution of use cases to support the needs of various businesses within the government.

Must Have:

Background in Computer Science, Data Science, or AI/ML (student or recent grad is good).
Familiarity with Python and libraries like pandas, scikit-learn, or PyTorch.
Exposure to LLM frameworks (DSPy, LangChain, Hugging Face, or equivalent).
Comfortable working with Databricks / MLflow or other cloud ML environments.
Detail-oriented with strong organizational skills for tracking experiments.

Key Responsibilities

Run and Monitor Inferences
Execute batch inference jobs on Databricks and other environments.
Troubleshoot inference issues, log results, and escalate model anomalies.
Pipeline & Evaluation Support
Assist with running DSPy pipelines and loading custom models/configs.
Support evaluation runs using internal metrics
Track and summarize performance metrics for inference experiments.
Data Handling & Experimentation
Help prepare and clean legal text datasets for inference and evaluation.
Annotate outputs to support error analysis and benchmarking.
Maintain reproducible scripts/notebooks for inference runs.

Evaluation Criteria:

Technical Skills - 50%
LLM frameworks - 25%
Databricks/MLflow - 25%

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More about this job

Responsibilities

Run and monitor batch inference jobs, troubleshoot issues, record results, and escalate model anomalies across Databricks and other environments. Support DSPy pipelines and model evaluations, prepare legal text datasets, analyze outputs, track performance metrics, and maintain reproducible scripts and notebooks.

Requirements

The posting seeks a candidate with a background in computer science, data science, or AI/ML, and familiarity with Python and libraries such as pandas, scikit-learn, or PyTorch. Candidates should have exposure to LLM frameworks, experience or familiarity with Databricks, MLflow, or other cloud ML environments, and strong attention to detail and organizational skills.

Skills

Python
Pandas
Scikit-Learn
PyTorch
Large Language Models
DSPy
LangChain
Hugging Face
Databricks
MLflow
Batch Inference
Model Evaluation
Data Cleaning
Experiment Tracking
Error Analysis
Legal Text Data

Visa sponsorship

Not detected in the job text

Hiring contact email

anila.dada@amyantek.com

Keywords

Artificial Intelligence
Machine Learning
Data Science
Computer Science
Python
Pandas
Scikit-Learn
PyTorch
Large Language Models
DSPy
LangChain
Hugging Face
Databricks
MLflow
Cloud Machine Learning
Batch Inference
Inference Monitoring
Model Evaluation
Performance Metrics
Data Cleaning
Legal Text Datasets
Error Analysis
Benchmarking
Experiment Tracking
Reproducible Notebooks
Data Ingestion
Data Governance
Data Quality
Ontario Data Platform
Ontario Public Service

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