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Added 1 day ago
FO
Data Advisor
Federation of Canadian Municipalities
Ottawa, ON · Greater Ottawa Metropolitan Area
- Full-time
…following areas: monitoring, evaluation, and organizational learning, funding program design and operations, program reporting and performance…
Added 1 day ago
PS
Senior Manager Cybersecurity - Governance Risk and Compliance
Professional Staffing
Toronto, ON · Greater Toronto Area, Canada
- $140,000 to $160,000 CAD / year
- Full-time
Lead cybersecurity strategy and governance for the secure adoption of Artificial Intelligence, Generative AI, machine learning, automation, and other emerging technologies.
Added 1 day ago
W
Software Development Engineer - Agent Factory
Workday
Vancouver, BC · Canada, BC, Vancouver
- Full-time
Agent Factory is where Workday’s next chapter gets built. We’re forming small, senior, cross-functional AI teams that bring together product leaders, machine learning engineers, and…
Added 1 day ago
SE
Manager, MX Sales Platform
Samsung Electronics
Mississauga, ON
- Full-time
Subsidized Cafeteria; including free Starbucks coffee/latte machine
Added 1 day ago
NS
Senior DevOps Engineer, AI Platform
Network Solutions
Canada
- Full-time
We are looking for a hands-on Senior DevOps Engineer to build and operate the infrastructure powering our AI platforms, agent runtimes, web applications, backend services, APIs, and shared…
Added 1 day ago
TC
Junior AI Engineer
The Citco Group Limited
Halifax, NS
- Full-time
…and enhancement of AI-powered solutions under the guidance of senior engineers leveraging large language models, natural language processing, document processing services, machine learning,…
Added 1 day ago
ED
Senior Data Platform Administrator - EN 533
Export Development Canada | Exportation et développement Canada
Ottawa, ON
- $96,557 to $128,743 CAD / year
- Full-time
Professional Development: Take advantage of our continuous learning opportunities, including training programs, workshops and language training
Added 1 day ago
C
Director, AI Delivery
CIBC
Toronto, ON
- Full-time
…also bring broader experience in artificial intelligence and machine learning…
Added 1 day ago
B
Sales Technology Excellence and Enablement Specialist
BD
Mississauga, ON
- Full-time
Work collaboratively with stakeholders at all levels within the organization ranging, from business users to senior management.
Added 1 day ago
O
Senior Product Manager
Oracle
Kitchener, ON
- $81,700 to $131,700 CAD / year
- Full-time
–Works with senior team members to identify potential solutions tied to OKRs and Key Performance Indicators (KPIs).
Added 1 day ago
T
Senior Data Engineer
TriMech
Oakville, ON
- Full-time
Support AI and machine-learning initiatives and evaluate emerging technologies for practical business value.
Added 1 day ago
R
RCI-ROCG-43306 Technical Product Manager (Computer Vision/AI/ML/Image Analysis) (Healthcare/Medical Device/Digital Health/Life Science)
Rangam
Mississauga, ON
- $64 to $66 CAD / hour
- Contract
Added 1 day ago
DI
MLOps Engineer – Databricks (1896) $90-100hr
Direct IT Recruiting Inc.
Toronto, ON
- $90 to $100 CAD / hour
- Contract
Define and operationalize the AI delivery model, including reusable implementation patterns, reference solutions, and engineering standards for RAG, agentic, and machine learning solutions.
Added 1 day ago
ZT
Applications Engineer Senior
Zebra Technologies
Montreal, QC
- Full-time
more senior colleagues, this person contributes to technical analyses, planning, and design efforts that
Added 1 day ago
V
Senior Data Scientist
Visa
Toronto, ON
- Full-time
Experience building and deploying machine learning models to production, focusing on modular, scalable, and maintainable models.
Added 1 day ago
N
Automation Engineer Co-op/Intern
Nokia
Ottawa, ON
- Full-time
Knowledge of Artificial Intelligence and Machine Learning concepts gained through coursework, projects, or practical experience.
Added 1 day ago
T
Senior Manager, Data Science
TD
Toronto, ON
- Full-time
Partner with business leaders to identify and prioritize high-value machine learning, artificial intelligence, and advanced analytics opportunities.
Added 1 day ago
C
AI Product Owner Director
CIBC
Toronto, ON
- Full-time
Leadership Partnership – Collaborate with the Senior Director to report on portfolio progress, ROI realization, and capacity planning for leadership.
Added 1 day ago
A
Associate Director, Automation & Innovation
AstraZeneca
Mississauga, ON · Canada - Mississauga
- Full-time
…Do you see yourself translating the latest advances in AI, machine learning and NLP into decisions that accelerate development and sharpen our strategic focus across a global R&D…
Added 1 day ago
WT
Senior Software Developer, ML Platform & Infrastructure
Wealthsimple Technologies
Toronto, ON
- $152,000 to $189,000 CAD / year
- Full-time
The Machine Learning Infrastructure & Platform team builds the foundational architecture powering AI and GenAI initiatives across Wealthsimple. We sit at the intersection of production…
Added 1 day ago
GS
Systems Designer - Ingénieur/développeur systèmes
Grantek Systems Integration
Montreal, QC
- Full-time
…design, Network design, Database design, Vision system design, Machine Safety system design, Servo motion control, Information Solution design, MES design, ERP connector development,…
Added 1 day ago
G
Systems Designer - Ingénieur/développeur systèmes
Grantek
Montreal, QC
- Full-time
…design, Network design, Database design, Vision system design, Machine Safety system design, Servo motion control, Information Solution design, MES design, ERP connector development,…
Added 1 day ago
A
MCP/AI Developer
Autodesk
Toronto, ON · AMER - Canada - Ontario - Toronto - University Ave
- Full-time
As an MCP/AI Developer you will build end-to-end features of that platform: MCP tools, agentic workflows, and the services behind them. You'll work hands-on across a modern, cloud-enabled…
Added 2 days ago
E
Senior Cloud Platform Engineer (AWS), AI Infrastructure - Evinova
Evinova
Mississauga, ON
- Full-time
The Machine Learning and Artificial Intelligence Operations team (ML/AI Ops) is the cloud platform engineering team responsible for building and operating the infrastructure that enables…
Added 2 days ago
Senior Agentic AI Engineer- Physical AI hub, Kitchener
Siemens
Kitchener, ON
We are seeking a Senior Agentic AI Engineer to build the harness reasoning, monitoring, recovery, and completion-gating capabilities for the Physical AI Runtime. This engineer will design…

Wealthsimple Technologies

Senior Software Developer, ML Platform & Infrastructure

Toronto, ON, Canada

$152,000 to $189,000 CAD / year · Full-time

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Job details

Pay: $152,000 to $189,000 CAD / year
Job type: Full-time
Experience: 7+ years of software engineering experience in ML Infrastructure, MLOps, ML Tooling, or Data Platform engineering.
Posting language: English
Posted: Oct 2, 2026

Original job description

Build something people love

Wealthsimple is Canada’s leading financial innovator. The company offers a full suite of simple, sophisticated financial products across managed investing, do-it-yourself trading, cryptocurrency, tax filing, spending and saving. Wealthsimple currently serves more than 4 million Canadians and holds over $155 billion in assets under administration. The company was founded in 2014 by a team of financial experts and technology entrepreneurs, and is headquartered in Toronto, Canada.

We're proud of what we've built - and we're just getting started. Read our Culture Manual and learn more about how we work.

ML Platform & Infrastructure Team

The Machine Learning Infrastructure & Platform team builds the foundational architecture powering AI and GenAI initiatives across Wealthsimple. We sit at the intersection of production MLOps and cutting-edge GenAI enablement.

As our AI footprint expands rapidly, our priority is evolving our robust MLOps foundations into a scalable, high-performance LLM serving and routing platform. We build self-serve systems that allow Data Scientists and Engineers to host open-source LLMs reliably, optimize inference latencies, manage GPU infrastructure, and benchmark model performance safely in production.

The Role

We are looking for an experienced MLOps or ML Platform Engineer who is excited to pivot their deep background in model orchestration, serving, and platform tooling toward solving the unique challenges of LLM inference and infrastructure.

In this role, you will bridge the gap between traditional MLOps (model lifecycles, pipeline orchestration, serving infrastructure) and modern GenAI stack requirements (vLLM, GPU cluster management, intelligent model routing, and automated Evals). You will take end-to-end ownership of setting the technical direction for operating enterprise-grade LLM systems company-wide.

In this role, you will have the opportunity to:

Turn MLOps expertise to GenAI: Transition traditional ML lifecycle and serving patterns into state-of-the-art LLM inference engines and GPU orchestration systems.
Build model-routing architecture: Design low-latency routing frameworks (e.g., LiteLLM integration) to dynamically direct requests across managed cloud providers (AWS Bedrock) and self-hosted open-source models.
Provision & scale GPU infrastructure: Architect and manage high-performance GPU serving environments on Kubernetes using engines like vLLM, Ray, and Triton.
Develop evaluation & benchmarking tooling: Build automated Evals and observability frameworks to empower engineers and data scientists to validate model quality, latency, and drift against production requirements.
Empower self-serve ML across Wealthsimple: Partner with product engineering and data science teams to build framework-agnostic platform tooling that abstracts infrastructure complexity.
Drive cost & performance optimization: Improve price-performance across self-hosted and managed inference by optimizing capacity, utilization, batching, routing, and model selection while meeting quality and reliability objectives

We are looking for people who have:

7+ years of software engineering experience in ML Infrastructure, MLOps, ML Tooling, or Data Platform engineering.
Deep experience in MLOps/ML Platform practices: Proven track record building and operating self-serve ML platforms, model registry workflows, experiment tracking, or production serving infrastructure (Kubeflow, MLflow, Ray, Triton, SageMaker).
Strong platform fundamentals: Advanced proficiency in Python, container orchestration via Kubernetes, infrastructure-as-code (Terraform), and cloud provider ecosystem (AWS).
Strong appetite to specialize in LLM serving: A genuine desire to leverage your existing MLOps skillset to tackle LLM-specific challenges (vLLM, model routing, prompt engineering tooling, vector databases, GPU memory optimization, or LLM evaluation frameworks).
Backend performance & observability focus: Experience designing highly available, observable microservices (e.g., FastAPI) handling real-time, low-latency requests.
End-to-end technical ownership: Proven capability to lead architectural roadmaps, guide multi-functional projects with high autonomy, and maintain complex platform systems for the long run.

Nice-to-haves (or areas you will learn on the job):

Direct experience serving open-source Large Language Models in production (vLLM, SGLang, TensorRT-LLM, Dynamo).
Hands-on work with CUDA, GPU partitioning, or distributed inference frameworks (Ray Serve).
Familiarity with vector search and retrieval engines (Elasticsearch, Qdrant, Pinecone).

Our Stack Includes:

Container & Infrastructure: Kubernetes, Terraform, AWS GPU Infrastructure
ML Serving & LLM Tooling: vLLM, Ray, Triton, LiteLLM, AWS Bedrock, MLflow, SageMaker
Languages & Frameworks: Python, FastAPI, PyTorch
Data & Streaming: Kafka, Postgres, Redshift, Snowflake

Why Wealthsimple?

🌸 Top-tier health benefits and life insurance

📈 Long-term group savings with employer match, through Wealthsimple for Business

🌴 20 vacation days, 4 wellness days, and unlimited sick and mental health days per year*

✈️ 90 days away: work outside Canada for up to 90 days per year*

👥 Employee resource groups, including Rainbow (2SLGBTQ), Women of WS, and Black at WS

🌎 We are a hybrid team with over 1,500 employees across North America. The people are one of the best parts of working here: you'll collaborate with incredibly talented, curious, and driven teammates who are deeply committed to doing great work.

*Unlimited paid sick days, Wellness Days and the 90 day away program do not apply to certain roles.

ICYMI

Technology & Innovation at Wealthsimple: We move quickly and build thoughtfully. That means we're always looking for better ways to work - whether that's new tools, AI, or rethinking how we approach a problem. We don't expect you to have all the answers, but we do expect curiosity and a willingness to evolve alongside the products we're building.

Inclusion Statement: We're building products for a diverse world, and we need a diverse team to do it well. We strongly encourage applications from everyone, regardless of race, religion, colour, national origin, gender, sexual orientation, age, marital status, or disability status.

Accessibility Statement: We're committed to an accessible hiring experience. If you need any accommodations throughout the interview process, please let us know - we'll work with you to make sure you have what you need. We also welcome any feedback on how we can better accommodate candidates with accessibility needs.

AI in Hiring: We may use artificial intelligence (AI) tools to support parts of our hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our team but don't replace human judgment – all final hiring decisions are made by people. If you have questions about how your data is used, reach out to us.

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More about this job

Responsibilities

You will build and scale foundational architecture for AI and GenAI initiatives, focusing on LLM inference engines and GPU orchestration. Additionally, you will develop self-serve platform tooling to empower data scientists and engineers to benchmark and deploy models reliably.

Requirements

The role requires 7+ years of software engineering experience in ML infrastructure, MLOps, or data platform engineering. Candidates must possess strong proficiency in Python, Kubernetes, and cloud infrastructure, along with a deep interest in LLM serving and performance optimization.

Skills

MLOps
Machine Learning Infrastructure
Python
Kubernetes
Terraform
AWS
vLLM
Ray
Triton
FastAPI
PyTorch
Model orchestration
GPU infrastructure
LLM inference
Observability
Data platform engineering

Benefits

Health benefits
Life insurance
Group savings with employer match
20 vacation days
4 wellness days
Unlimited sick days
Unlimited mental health days
90 days away program
Equity compensation

Visa sponsorship

Not detected in the job text

Keywords

MLOps
Machine Learning
GenAI
LLM
Infrastructure
Kubernetes
Terraform
AWS
Python
FastAPI
PyTorch
vLLM
Ray
Triton
LiteLLM
MLflow
SageMaker
Kafka
Postgres
Redshift
Snowflake
GPU
CUDA
Vector databases
Model routing
Observability
Microservices
Data platform
Inference
Benchmarking

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