Data scientist jobs in Toronto, ON and nearby

Within 25 km

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Added 1 month ago
RE
Data Scientist
Rodan Energy Solutions Inc.
Mississauga, ON
- Full-time
Hybrid: 3 days in office in Mississauga, Ontario
Added 1 month ago
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Senior Data Scientist
dentsu
Toronto, ON
- Full-time
The Senior Data Scientist, will be part of a cross-functional team, specifically focused on developing mixed marketing models for our clients. The ideal candidate is both well versed in the…
Added 1 month ago
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Senior Data Scientist
Visa
Toronto, ON
- Full-time
Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager
Added 1 month ago
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Data Scientist, Commercial Price Modelling
Aviva Canada
Toronto, ON
- Full-time
As a Data Scientist on our Commercial P&C Price Modelling & Sophistication team, you'll build models and data-driven solutions that improve customer experience, support business decisions,…
Added 1 month ago
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Data Scientist, Commercial Price Modelling
Aviva Canada
Markham, ON
- Full-time
As a Data Scientist on our Commercial P&C Price Modelling & Sophistication team, you'll build models and data-driven solutions that improve customer experience, support business decisions,…
Added 1 month ago
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Applied Machine Learning Scientist I
TD
Toronto, ON
- Full-time
We’re looking for a highly motivated Applied Machine Learning Scientist to join our AI2 team. In this role, you’ll drive the development and deployment of ML solutions that power…
Added 1 month ago
Data Scientist, Commercial Price Modelling
Aviva
Toronto, ON · Markham, ON
As a Data Scientist on our Commercial P&C Price Modelling & Sophistication team, you'll build models and data-driven solutions that improve customer experience, support business decisions,…
Added 1 month ago
Senior Data Scientist
Scotiabank
Toronto, ON
Within this department, the Senior Data Scientist is responsible for solving complex business problems, using quantitative approaches with a unique blend of analytical, mathematical and…
Added 1 month ago
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Senior Machine Learning Engineer
Autodesk
Toronto, ON
- Full-time
Must have worked on Snowflake Cost optimization scenarios
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Data Scientist II
TD
Toronto, ON
- Full-time
The Data Scientist II, Branch Analytics will design, build, and deploy advanced analytics solutions across cloud-based platforms, translating complex business problems into production-ready…
Added 1 month ago
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Senior Data Architect
Encore Technical Solutions Inc.
Toronto, ON
- Contract
…systems onto modern, cloud-based platforms. They need a hands-on Data Architect to design a data architecture on Azure that's scalable, secure and well governed, and that supports…
Added 1 month ago
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Senior Data Architect
Manulife
Toronto, ON
- Full-time
Work arrangement: Hybrid - 3 days in office, 2 days from Home; Remote working option is not available
Added 1 month ago
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Sr. Data Scientist
Tundra Technical Solutions
Mississauga, ON
- $75 to $85 CAD / hour
- Contract
Senior Data Scientist role within our client's Advanced Analytics team. This posting is for two headcount and both are end-to-end data science roles and are interchangeable by design.
Added 1 month ago
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Data Scientist
Dexian
Mississauga, ON
- $75 to $85 CAD / hour
- Contract
Have 8–10 years of data science/analytics experience.
Added 1 month ago
Data Scientist (Askuity division)
The Home Depot
Toronto, ON
As a Data Scientist on the Askuity team, you will design, build, and deploy advanced analytics and machine learning solutions that drive measurable impact for The Home Depot and its…
Added 1 month ago
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Data Scientist III - Financial Crimes Network Analytics (ATH 5556)
TD
Toronto, ON · Markham, ON
- Full-time
Data Scientist III ( Financial Crimes Network Analytics )
Added 1 month ago
AC
Pharmaceutical Data Scientist
Amaris Consulting | Part of Mantu
Toronto, ON
- Full-time
We are seeking a highly skilled Data Scientist to join our pharmaceutical analytics and digital innovation team. This role plays a key part in transforming scientific, clinical,…
Added 1 month ago
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Data Scientist III, Global Supplier Technology
Wayfair
Toronto, ON
- $172,180 to $185,424.5 CAD / year
- Full-time
As a Data Scientist III on this team, you'll turn that map into decisions. You'll define how we measure and rank huddles, figure out why products win or lose within them, and show whether…
Added 1 month ago
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Data Scientist III - Financial Crimes Network Analytics (ATH 5556)
TD
Toronto, ON
- Full-time
Data Scientist III ( Financial Crimes Network Analytics )
Added 1 month ago
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Applied Machine Learning Scientist II
TD
Toronto, ON
- Full-time
…includes gathering, analyzing, and modeling a wide range of data, applying mathematical models/techniques and tools, and utilizing software engineering best practices to develop and…
Added 1 month ago
HI
Data Scientist
HISH IT SERVICES
Toronto, ON
- $85 CAD / hour
- Contract
…and profitability analytics, you will help clients mine their data, surface opportunities, and design the experiments and attribution models that prove what works. The preliminary…
Added 1 month ago
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I&IT Data Scientist I
Metrolinx
Toronto, ON
- Full-time
The Enterprise AI & Data Centre of Excellence (CoE) within I&IT delivers trusted data, analytics, and AI solutions that help Metrolinx make better decisions and improve business outcomes.…
Added 1 month ago
Senior Machine Learning Engineer, Recommendations
Lyft
Toronto, ON
Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role
Added 1 month ago
Senior Data Scientist I
Bell
Toronto, ON
For work arrangements that are ‘Hybrid’, successful candidates must be based in Canada and report to a set Bell office for a minimum of 3 days a week
Added 1 month ago
AT
lead data scientist
ApoSys Technologies Inc.
Mississauga, ON
- Full-time
Conduct research regarding availability and suitability of data

Autodesk

Senior Machine Learning Engineer

Toronto, ON, Canada
AMER - Canada - Ontario - Toronto - University Ave, Canada

For Canada based roles, we expect a starting base salary between $123,000 and $180,400. · Full-time

Apply on autodesk.wd1.myworkdayjobs.com About employer

Applications open in a new tab.

Job details

Pay: For Canada based roles, we expect a starting base salary between $123,000 and $180,400.
Job type: Full-time
Experience: 5+ years of machine learning engineering, or data engineering, or related experience, including significant experience developing production systems
Posting language: English
Posted: Oct 7, 2026

Original job description

Job Requisition ID #

26WD101236

Position Overview

We are looking for an exceptional Machine Learning Engineer to design, build, operationalize, and scale production-grade AI/ML and Agentic AI systems at Autodesk For Go-to-market intelligence function.

The mission of the team is to empower decision makers and the broader data communities through trusted data assets and scalable self-serve intelligence. The focus of this role will be engineering end-to-end AI/ML solutions - including feature engineering, data cleansing, contributing in model training process, model deployment, model validations, model evaluation, inference pipelines, and production orchestration.

You will work at the intersection of machine learning, data & analytics engineering, You will collaborate closely with data engineers, data scientists, analysts, platform teams, and business stakeholders to deliver reusable intelligent data products at enterprise scale.

The role requires a strong engineering mindset, hands-on experience building production ML systems, and the ability to evaluate and integrate rapidly evolving AI technologies while maintaining high standards for quality, observability, security, governance, cost efficiency, and operational reliability.

Responsibilities

Design, develop, test, deploy, and maintain production-grade ML pipelines supporting enterprise-scale use cases
Develop reusable ML services and components
Develop robust model evaluation frameworks covering dimensions such as accuracy, relevance, groundedness, consistency, latency, throughput, robustness, and cost
Design automated evaluation pipelines using deterministic metrics, model-based evaluation, curated datasets, regression testing, and human evaluation where appropriate
Build and maintain distributed processing pipelines capable of handling large volumes of documents, web content, structured data, and unstructured data efficiently
Design and optimize distributed pipeline and cloud orchestration for large-scale AI workloads using appropriate workflow orchestration and cloud-native technologies
Implement resilient processing patterns including concurrency management, queue-based architectures, checkpointing, retries, failure recovery, rate limiting, and idempotent processing
Optimize AI/ML systems for latency, throughput, scalability infrastructure utilization, and model inference cost
Partner with platform engineering teams to integrate AI applications with the relevant platforms, APIs, identity and access management, monitoring, and deployment infrastructure
Implement appropriate MLOps and LLMOps practices, including model and prompt versioning, experiment tracking, evaluation, deployment automation, monitoring, rollback mechanisms, and lifecycle management
Build comprehensive observability and monitoring mechanisms across ML pipelines, covering pipeline health, model performance, data quality, failures, and cost
Implement mechanisms to identify and manage model drift, data drift, quality degradation, and upstream data changes
Build modular frameworks and reusable components that enable teams to develop new capabilities through self-service patterns rather than one-off implementations
Work closely with data scientists, data engineers, analysts, product teams, and business stakeholders to translate business problems into appropriate ML architectures and implementation strategies
Translate complex ML system designs, model behavior, limitations, and trade-offs into business-appropriate representations for technical and non-technical stakeholders
Support experimentation and rapid prototyping while ensuring successful solutions can transition into maintainable, production-grade systems
Contribute to engineering standards, reference architectures, design reviews, code reviews, technical documentation, and AI/ML engineering best practices

Minimum Qualifications

Bachelor's degree in Computer Science, Engineering, Machine Learning, Data Science, Information Systems, or a related technical discipline
5+ years of machine learning engineering, or data engineering, or related experience, including significant experience developing production systems
Demonstrated experience designing and operating production ML systems rather than only experimentation or notebook-based model development
Strong programming skills in Python, with the ability to develop modular, testable, maintainable, and production-quality software

Working experience with Snowflake, Hands-on experience with Snowflake utilities, Snow SQL, Snow Pipe. Must have worked on Snowflake Cost optimization scenarios
Experience with workflow orchestration technologies such as Airflow or comparable orchestration frameworks
Have experience on Data transformation tools like DBT
Hands-on experience building and deploying machine learning inference pipelines and services
Experience designing distributed data or ML processing pipelines for high-volume workloads
Experience deploying workloads into a major cloud environment, preferably AWS, and working with cloud services for compute, storage, event processing, monitoring, and distributed execution
Experience with Git-based software development workflows, code reviews, branching strategies, and collaborative engineering practices
Familiarity with MLOps concepts, including experiment tracking, model lifecycle management, deployment, model monitoring, reproducibility, and versioning
Experience working with structured and unstructured data and designing preprocessing, enrichment, and transformation pipelines.
Strong analytical, debugging, and problem-solving skills with the ability to diagnose issues across application, model, pipeline, and infrastructure layers
Strong written and verbal communication skills and the ability to collaborate effectively with engineering, data science, product, and business stakeholders
Ability to work effectively with geographically distributed teams across multiple time zones
Familiarity with Agile/Scrum software development practices.
Experience working with remote teams spread across multiple time-zones

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 $123,000 and $180,400. 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 on autodesk.wd1.myworkdayjobs.com About employer

More about this job

Responsibilities

Design, build, and scale production-grade AI/ML and Agentic AI systems to support go-to-market intelligence. Collaborate with cross-functional teams to develop reusable ML services, evaluation frameworks, and robust data pipelines at enterprise scale.

Requirements

Requires a bachelor's degree in a technical field and at least 5 years of experience in machine learning or data engineering. Candidates must have strong Python programming skills and hands-on experience with Snowflake, cloud environments, and MLOps practices.

Skills

Python
Snowflake
Snow SQL
Snow Pipe
Airflow
DBT
Machine Learning
MLOps
LLMOps
Cloud orchestration
AWS
Data engineering
Distributed systems
Model evaluation
Feature engineering
Data pipelines

Benefits

Annual cash bonuses
Stock grants

Visa sponsorship

Not detected in the job text

Keywords

Machine Learning
AI
Agentic AI
Python
Snowflake
Snow SQL
Snow Pipe
Airflow
DBT
MLOps
LLMOps
AWS
Cloud Computing
Data Engineering
Feature Engineering
Model Deployment
Inference Pipelines
Distributed Systems
Data Governance
Observability
Agile
Scrum
Data Science
Automation
Scalability
Model Drift
Prompt Versioning
Infrastructure
API
Identity and Access Management

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Data scientist jobs in Toronto, ON and nearby

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