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Added 4 mins ago
Manager, Enterprise
BrainStation
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Genuine enthusiasm for in-person work and collaboration; this role follows a hybrid model with four or more days per week in the office
Added 4 mins ago
BC
Field Specialist – PTUS
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Toronto, ON
- $95,000 to $140,000 CAD / year
- Full-time
…Toronto, ON. The Field Specialist will be part of the Delivery Partner integrated project team responsible for performing construction field engineering assignments of a varied nature the…
Added 4 mins ago
HM
Family Practitioner/General Practitioner
Health Match BC
Ucluelet, BC
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COMMUNITY HEALTH WORKER I
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Added 1 hour ago
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Automotive Service Technician - North Vancouver
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North Vancouver, BC
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CH
Advisor - People Relations
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Edmonton, AB
- $37.12 to $55.68 CAD / hour
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Added 2 hours ago
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Edmonton, AB
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shift supervisor - Store# 49300, YORKDALE MALL KIOSK
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…by providing legendary customer service with prompt service, quality beverages and products, and maintaining a clean and comfortable store environment. You will be responsible for modeling…
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Provision

Machine Learning Engineer

Toronto, ON, Canada

$170K - $250K CAD

Apply on provision.com About employer

Applications open in a new tab.

Job details

Pay: $170K - $250K CAD
Posting language: English

Original job description

← Careers

Machine Learning Engineer

Hybrid · Toronto

Salary

$170K - $250K CAD

Equity

0.05% - 0.15%

Role

Machine learning engineering

About Provision

Provision helps construction teams understand complex project documents, identify risk, and turn fragmented information into decisions. We are building an AI-native product for work where accuracy, evidence, and trust matter.

The Role

We are looking for a Machine Learning Engineer to own applied ML systems from problem definition through production. You will work closely with engineering, product, and domain experts to improve how Provision understands construction documents, retrieves evidence, evaluates answers, and learns from real customer workflows.

This is a hands-on role for someone who can move between models, data, evaluation, software, and product judgment. The goal is not a demo; it is reliable intelligence that customers can use in consequential work.

What You Will Do

Build and operate production ML and AI systems for document understanding, retrieval, extraction, and reasoning.
Design evaluation datasets, metrics, experiments, and error-analysis loops that make quality measurable.
Improve data pipelines and feedback loops while protecting the integrity and provenance of training and evaluation data.
Make pragmatic decisions across prompting, retrieval, model selection, fine-tuning, and conventional ML approaches.
Build observability for model behavior, cost, latency, reliability, and regressions.
Partner with product and construction experts to turn ambiguous customer problems into testable technical plans.
Contribute production-quality Python and collaborate across the broader application stack.

What We Are Looking For

Experience shipping and operating ML or AI systems used by real customers.
Strong Python and software-engineering fundamentals, including testing, debugging, APIs, and data systems.
Practical experience with modern language or multimodal models, retrieval systems, and evaluation methods.
Sound judgment about data quality, experimentation, failure modes, and the limits of model outputs.
Ability to explain technical tradeoffs clearly and work closely with product and domain partners.
Comfort operating with ownership, pace, and ambiguity in an early-stage environment.
Willingness to work with the team in person in Toronto.

Interview Process

Introductory call · 20 minutes: A focused conversation about Provision, the role, your experience, and mutual fit.
Online technical interview · 2 hours: A collaborative ML problem covering problem framing, evaluation, data, system design, and production tradeoffs. We will share the format in advance.
In-office interview day: Meet the team and learn how we collaborate. The day includes a whiteboarding session focused on designing and improving a production ML system.
References and offer: Complete focused references, resolve any remaining questions, and move to an offer when there is a strong mutual fit.

We share the purpose of each conversation in advance, collect written feedback before debriefing, and aim to move quickly between stages.

Apply through our short form and we'll be in touch.

Apply now

Want to learn more about how we work? Read how we build at Provision →

Provision does not use AI to screen, assess, or select applicants. Accommodation is available upon request throughout the recruitment process.

Apply on provision.com About employer

More about this job

Responsibilities

The Machine Learning Engineer at Provision will build and run production AI systems that read and reason over construction documents. They will design evaluations, improve data pipelines and feedback loops, and work with product and construction experts.

Requirements

Candidates need experience shipping and operating ML or AI systems used by real customers, strong Python and software engineering skills, and practical work with modern language or multimodal models and retrieval. Sound judgment on data quality, experimentation and failure modes is also required.

Skills

Python
Machine learning
Large language models
Multimodal models
Retrieval systems
Model evaluation
Experiment design
Error analysis
Data pipelines
Data quality
API development
Software testing
Debugging
Production ML
Model observability
Prompt engineering
Fine-tuning
Document understanding
Information extraction
Technical communication

Benefits

Equity

Keywords

Machine Learning Engineer
machine learning
AI engineering
applied ML
Python
LLM
multimodal models
retrieval
RAG
evaluation
document understanding
information extraction
data pipelines
MLOps
observability
construction technology
construction tech
fine-tuning
prompt engineering
Toronto

Perks

Stock or equity

Languages

English

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Work requirements

Jobs in Canada