Engineering managers jobs in Vaughan, ON and nearby

Engineering managers jobs within 25 km of Vaughan, ON, Canada. Nearby towns and cities are included. Distances are straight-line, not driving distances.

Counted Nov 1, 2026

Hiring at a glance

View jobs

Open jobs: 167
Employers: 110

Advertised starting pay

Average starting payCAD / year: $150,877Across 25 listings

Employer-advertised starting pay, not employee salaries. Currencies and pay periods stay separate.

Where work happens

Remote: 0%0 listings
Hybrid: 51%86 listings
On-site: 47%79 listings

Not specified: 1% (2 listings)

Employers hiring include AtkinsRéalis (6), Stripe (6), Lyft (4).

Sources & calculation notes

These figures describe the listings on this role page at the date shown, not the whole job market. Listings can change.

Employer-listed minimums from at least 10 listings per currency and pay period. These are advertised starting amounts, not employee salaries. Jobs without a minimum and unusual amounts are excluded.

Hybrid and on-site classifications may be inferred from descriptions. Check the original ad. How we count

Engineering managers jobs in Vaughan, ON and nearby

Within 25 km

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Added 12 days ago
A
Engineering Manager, ML Infrastructure & Operations - Forma Generative AI
Autodesk
Toronto, ON
- Full-time
As the Engineering Manager for ML Infrastructure & Operations in Forma Generative AI, you will lead the team responsible for the systems that power our ML lifecycle, from large-scale…
Added 12 days ago
HT
Engineering Manager - CoCounsel Tax
Hudson Talent Solutions
Toronto, ON
- Full-time
…generation. Working alongside private bankers and external asset managers, the group structures and administers trusts for ultra-high-net-worth families. Rather than holding client deposits…
Added 12 days ago
Deputy Project Engineering Manager
Alstom
Toronto, ON
Added 12 days ago
Security Engineering Manager
Varicent
Toronto, ON
Added 13 days ago
Engineering Manager, Dynamic Pricing
Lyft
Toronto, ON
Added 14 days ago
M
Director of Engineering - Mortgage Creditor Insurance
Manulife
Toronto, ON
- Full-time
…world-class customer and employee experiences through software and engineering skills. The customer is at the focus of everything we do, and millions of end users rely on our products…
Added 15 days ago
Engineering Manager, New User Experience
DoorDash Canada
Toronto, ON
Added 15 days ago
SI
Maintenance Engineering Manager
Synectics Inc.
Aurora, ON
- $70,000 to $90,000 CAD / year
- Full-time
Added 16 days ago
A
Engineering Manager
Actalent
Toronto, ON
- $120,000 to $147,000 CAD / year
- Full-time
Job Title: Engineering ManagerJob Description
Added 16 days ago
AM
Firmware Engineering Manager
Advanced Micro Devices, Inc
Markham, ON
- Full-time
Added 16 days ago
A
Firmware Engineering Manager
AMD
Markham, ON
- $140,800 to $211,200 USD / year
- Full-time
Added 16 days ago
Engineering Manager, Enterprise Systems
OpenTable
Toronto, ON
Added 16 days ago
CP
Security Engineering Manager
Check Point Software Technologies
Toronto, ON
- Full-time
Added 16 days ago
SC
Senior Systems Engineering Manager
SYSTRA Canada
Toronto, ON
- Full-time
SYSTRA Canada is part of the SYSTRA group, an international consulting and engineering group, a world leader in the design of transport infrastructures. SYSTRA Canada is an engineering and…
Added 16 days ago
A
Engineering Manager
Actalent
Toronto, ON
- $120,000 to $147,000 CAD / year
- Full-time
Job Title: Engineering ManagerJob Description
Added 16 days ago
J
Engineering Manager, Backend - International
Justworks
Toronto, ON
- Full-time
Added 16 days ago
Engineering Manager, Backend - International
Justworks
Toronto, ON
Added 16 days ago
Senior Engineering Manager, Release Engineering
PagerDuty
Toronto, ON
Added 18 days ago
PI
Engineering Manager (Mechanical Design)
Pack-Smart Inc.
Concord, ON
- Full-time
Engineering Manager (Mechanical Design) - Lead, Develop, and Elevate a High-Performance Design Team
Added 18 days ago
E
Senior Engineering Manager, Analytics
Emburse
Toronto, ON
- Full-time
As Senior Engineering Manager, Analytics, you will lead two data and analytics teams, Emburse Analytics and Travel Analytics,
Added 18 days ago
Engineering Manager, Terminal
Stripe
Toronto, ON
Added 18 days ago
EC
Senior Engineering Manager, Analytics
Emburse Chrome River
Toronto, ON
- Full-time
As Senior Engineering Manager, Analytics, you will lead two data and analytics teams, Emburse Analytics and Travel Analytics, t
Added 18 days ago
E
Senior Engineering Manager, Analytics
Emburse
Toronto, ON
- Full-time
As Senior Engineering Manager, Analytics, you will lead two data and analytics teams, Emburse Analytics and Travel Analytics,
Added 20 days ago
SL
Engineering Manager
Sun Life
Toronto, ON
- Full-time
Added 22 days ago
WA
Director of Engineering - Hilton Toronto
Waldorf Astoria Kuwait
Toronto, ON
- Full-time
…what you’ll do every time you come to work! As a Director of Engineering, you’re not just responsible for the safety and functionality of the property – you’re spreading the light and…

Autodesk

Engineering Manager, ML Infrastructure & Operations - Forma Generative AI

Toronto, ON, Canada

For Canada based roles, we expect a starting base salary between $158,000 and $231,000. · Full-time

Apply About employer

Applications open in a new tab.

Job details

Pay: For Canada based roles, we expect a starting base salary between $158,000 and $231,000.
Job type: Full-time
Apply by: Nov 18, 2026
Experience: 2+ years of engineering people-management experience, including coaching engineers, setting priorities, and driving technical delivery
Posting language: English
Posted: Oct 19, 2026

Original job description

Job Requisition ID #

26WD101527

Position Overview

Autodesk is transforming how the AEC industry designs and builds through integration of Artificial Intelligence (AI) and Machine Learning (ML) across its products, including AutoCAD, Revit, and Forma.

As the Engineering Manager for ML Infrastructure & Operations in Forma Generative AI, you will lead the team responsible for the systems that power our ML lifecycle, from large-scale training and experimentation through deployment, inference, and production operations. You will set technical direction for scalable, reliable, and cost-efficient ML infrastructure while partnering with platform teams on shared capabilities. You will establish the tooling, observability, and automated evaluation infrastructure needed to deliver AI models confidently and operate them reliably in production.

Your team will determine how quickly and reliably we can move from promising ML research to models operating at scale in Autodesk products. You will work closely with AI researchers, ML engineers, product teams, and platform organizations to make that possible.

Report: You will report to the Head of Engineering, ML - Forma Generative AI.

Location: We support hybrid work, and you work near our Toronto, Canada office. This role requires the ability to travel to team meetings, offsites, and conferences in the USA, Canada, and Europe.

Responsibilities

Lead, grow, and develop a team of ML engineers responsible for shared ML infrastructure and operations. Set clear priorities and expectations, coach engineers, and create opportunities for growth and increasing technical ownership
Own the infrastructure for large-scale ML training and experimentation, enabling researchers and ML engineers to run, scale, reproduce, and iterate on experiments efficiently
Own the infrastructure and workflows that move models from experimentation through product testing and production, enabling fast, safe, and reproducible deployment of new model versions
Define the architecture and optimization strategy for ML workloads as model size, data volume, compute requirements, and experiment velocity grow, with a focus on performance, utilization, and cost-efficiency
Own the operational health of shared ML systems in production, including observability, reliability targets, incident response, capacity planning, and continuous improvement
Partner with research engineering and platform teams to establish reusable infrastructure, deployment patterns, and production standards for ML systems
Build the infrastructure supporting model evaluation and release readiness, including automated regression testing, reproducible evaluation pipelines, versioning, lineage, and release gates, in partnership with Research, Product, and Trusted AI teams

Minimum Qualifications

BS/MS in Computer Science, Engineering, or equivalent practical experience
2+ years of engineering people-management experience, including coaching engineers, setting priorities, and driving technical delivery
Experience designing, building, and operating infrastructure for ML training, experimentation, and/or inference at scale
Experience designing and operating distributed systems in a major cloud environment (AWS, Azure, or GCP), including production observability, reliability, and capacity management
Strong software engineering, communication, and technical decision-making skills

Preferred Qualifications

Experience with distributed ML training, GPU workload orchestration, and/or high-performance inference systems
Experience building infrastructure for foundation models or other large-scale ML systems
Experience in the AEC industry, Autodesk, or AEC data and workflows
Evidence of staying current with fast-moving ML infrastructure technologies and applying new approaches pragmatically

The Ideal Candidate

You care deeply about reliability, performance, and cost efficiency across the ML lifecycle, and a low tolerance for production systems held together by hope
You communicate effectively across disciplines and levels, adapting your approach to build shared understanding with technical, product, and research audiences
You can move comfortably between people leadership, architecture, and problem-solving, making pragmatic build-vs-partner decisions
You create clarity in ambiguous technical areas by communicating effectively across research, engineering, product, and platform teams
You build teams with clear ownership, strong engineering standards, and room for engineers to grow

Learn More

About Autodesk

Welcome to Autodesk! Amazing things are created every day with our software – from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made.

We take great pride in our culture here at Autodesk – it’s at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world.

When you’re an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us!

Salary transparency

Salary is one part of Autodesk’s competitive compensation package. For Canada based roles, we expect a starting base salary between $158,000 and $231,000. Offers are based on the candidate’s experience and geographic location, and may exceed this range. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.

Belonging

We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: https://www.autodesk.com/company/global-belonging

In-Person Onboarding and Identity Verification

This role may require in-person onboarding and/or in-person ID verification.

Apply About employer

More about this job

Responsibilities

Lead and develop a team responsible for shared ML infrastructure, including large-scale training and experimentation, model deployment, production operations, and cost-efficient architecture. Establish reliable operational practices and automated evaluation and release workflows while partnering with research, product, and platform teams.

Requirements

Requires a bachelor's or master's degree in computer science, engineering, or equivalent practical experience, at least two years of engineering people-management experience, and experience operating scalable ML infrastructure and distributed cloud systems. Strong software engineering, communication, and technical decision-making skills are required; experience with distributed ML training, GPU orchestration, foundation models, or AEC workflows is preferred.

Skills

People Management
Machine Learning Infrastructure
ML Training and Experimentation
Model Deployment
Distributed Systems
Cloud Computing
Production Observability
Reliability Engineering
Capacity Planning
GPU Workload Orchestration
Distributed ML Training
High-Performance Inference
Automated Evaluation
Regression Testing
Cost Optimization
Technical Leadership

Benefits

Annual Cash Bonuses
Stock Grants

Visa sponsorship

Not detected in the job text

Keywords

Machine Learning
Generative AI
ML Infrastructure
ML Operations
Large-Scale Training
Experimentation
Model Deployment
Inference
Distributed Systems
AWS
Azure
GCP
GPU Workload Orchestration
Foundation Models
Observability
Reliability
Capacity Planning
Automated Evaluation
Regression Testing
Reproducible Evaluation Pipelines
Model Versioning
Data Lineage
Release Gates
Cost Efficiency
AEC
Autodesk Forma
AutoCAD
Revit

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