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Added 43 mins ago
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Axon Health

AI/ML Engineer

Ottawa, ON, Canada

Full-time

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Job details

Job type: Full-time
Apply by: Nov 7, 2026
Posting language: English
Posted: Oct 8, 2026

Original job description

AI/ML Engineer - Job Description

Help recovery, youth and family services organizations use AI safely on their most sensitive data. We're hiring an AI/ML Engineer to build the permission-aware knowledge graph and safety layer behind Axon Health's AI agent.

About Axon Health

Axon Health is the AI-native platform for community care: addiction treatment centres, recovery housing, foster care, family services, drug treatment courts and outpatient programs in Canada and the US. Our AI agent lets frontline staff ask questions in plain English, build dashboards and produce funder-ready reports from their organization's data. We build to HIPAA and PHIPA requirements and are working toward SOC 2.

About the role

You'll work alongside Hassan, who leads analytics and custom dashboards, on two connected areas. Together, you'll move our customers through four stages of analytics, each building on the last: descriptive (what happened), diagnostic (why it happened), predictive (what's likely next), and prescriptive (what to do about it, with Axon recommending actions automatically).

Customer analytics (descriptive and diagnostic). Turn what each customer needs to see into dashboards that show what happened and why, then into a self-serve feature on the Axon Health platform.
Predictive and prescriptive modelling. Build Axon Health's first predictive models, turn their outputs into recommended actions, and build the foundation to run them reliably.

What you'll do

Customer analytics

Gather each customer's analytics requirements and build dashboards that clinical stakeholders can use.
Build the pipelines and APIs that feed those dashboards into the Axon Health platform.
Help design and ship a drag-and-drop dashboard builder so customers can create their own views.

Predictive modelling

Work with leadership, clinical and product teams to pick the use cases worth modelling first.
Set up reproducible workflows for features, training, validation, and model versioning.
Build and validate models for outcomes such as relapse risk, readmissions, and discharge timing.
Deploy models into Axon Health, monitor them for drift and bias, and turn their outputs into recommended actions for care teams.
Record your time weekly against project activities (this role is supported by NRC-IRAP).

What you bring

2+ years in data science, ML, or analytics engineering, including at least one model or dashboard you took to production.
Strong Python (pandas, NumPy, scikit-learn) and SQL.
Hands-on MongoDB, including aggregation pipelines and indexing.
Sound ML fundamentals: feature engineering, cross-validation, choosing the right metrics, and handling imbalanced data.
Experience building dashboards for non-technical users and explaining results in plain language.
Experience with health data under PHIPA or HIPAA.
A degree in Computer Science, Statistics, or a related field, or equivalent experience.

Nice to have

Experience in behavioural health, addiction treatment, or rehabilitation services.
Experience building recommendation or decision-support systems.
Building embedded analytics or frontend charting features.
Setting up MLOps (model versioning, monitoring, retraining) at a small or growing organization.
Familiarity with fairness and bias assessment for clinical models.

How to apply

Send your resume to careers@axonhealth.io.

Axon Health is an equal opportunity employer. We welcome applicants of all backgrounds, including people with lived experience of addiction or mental health challenges. Accommodations are available on request throughout the hiring process, in line with the Accessibility for Ontarians with Disabilities Act (AODA).

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More about this job

Responsibilities

Build customer analytics dashboards, data pipelines, APIs, and self-service dashboard features for the Axon Health platform. Develop, validate, deploy, and monitor predictive models, then translate their outputs into recommended actions for care teams.

Requirements

Requires at least two years of experience in data science, machine learning, or analytics engineering, including taking a model or dashboard to production, along with strong Python and SQL skills and hands-on MongoDB experience. Candidates should understand core machine-learning methods, be able to build dashboards for non-technical users, and have experience with health data under PHIPA or HIPAA; a relevant degree or equivalent experience is required.

Skills

Python
SQL
MongoDB
Machine Learning
Predictive Modeling
Feature Engineering
Cross-Validation
Model Validation
Model Monitoring
MLOps
Dashboard Development
Data Pipelines
API Development
Data Visualization
Bias and Fairness Assessment
Healthcare Data Privacy

Visa sponsorship

Not detected in the job text

Keywords

Python
Pandas
NumPy
Scikit-Learn
SQL
MongoDB
Aggregation Pipelines
Indexing
Machine Learning
Predictive Modeling
Feature Engineering
Cross-Validation
Imbalanced Data
Model Versioning
Model Monitoring
MLOps
Data Pipelines
APIs
Dashboards
Embedded Analytics
Recommendation Systems
Decision-Support Systems
Healthcare Data
PHIPA
HIPAA
SOC 2
Fairness Assessment
Bias Monitoring
Behavioural Health
NRC-IRAP

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