ZipRecruiter

Log In

1

Machine Learning Data Associate Jobs in Mississauga, ON

KPMG

Manager, ML/AI Engineer, Data & AI

Toronto, ON

Collaborate with data engineers to ensure reliable, scalable data pipelines that support model ... Cloud AI / ML certifications (e.g., Azure AI Engineer Associate or better, AWS Machine Learning ...

KPMG

Manager, ML/AI Engineer, Data & AI

Toronto, ON

Collaborate with data engineers to ensure reliable, scalable data pipelines that support model ... Cloud AI / ML certifications (e.g., Azure AI Engineer Associate or better, AWS Machine Learning ...

Td

Applied Machine Learning Scientist II

Toronto, ON

CA$125K - CA$154K/yr

We're looking for a highly motivated Applied Machine Learning Scientist II to join our AI2 team. In ... Experience with structured and unstructured data, feature engineering, and model interpretability ...

Td

Senior Machine Learning Engineer

Toronto, ON · On-site

CA$170K - CA$250K/yr

Architect scalable machine learning and Gen AI systems that integrate with existing data platform and infrastructure, focusing on automation, operation efficiency, and reliability * Write clean ...

previous pagenext page

Showing results 21-40

All JobsMachine Learning Data Associate JobsMachine Learning Data Associate Jobs in Mississauga, ON

Machine Learning Data Associate information

What is a machine learning data associate?

Machine Learning Data Associates are professionals who support the development of machine learning models by preparing, labeling, and validating data sets. Their work ensures that data used for training algorithms is accurate, consistent, and properly annotated. They may also assist with data cleaning, quality checks, and sometimes basic data analysis tasks. This role is crucial in industries where high-quality labeled data is essential for building effective AI systems.

What are the key skills and qualifications needed to thrive as a machine learning data associate?

To thrive as a Machine Learning Data Associate, you need strong analytical skills, attention to detail, and a basic understanding of data annotation and labeling processes, often supported by a degree in computer science or a related field. Familiarity with data management tools, annotation platforms, and sometimes scripting languages like Python is typically required. Strong communication, collaboration, and problem-solving abilities help you work efficiently with data science teams and ensure high-quality outcomes. These skills and qualities are crucial for producing accurate datasets that directly impact the effectiveness of machine learning models.

How does a machine learning data associate typically collaborate with data scientists and engineers within a project team?

As a Machine Learning Data Associate, you play a vital role in supporting data scientists and engineers by annotating, cleaning, and organizing large datasets to ensure high data quality. You'll frequently communicate with team members to clarify labeling guidelines, provide feedback on data inconsistencies, and report any edge cases encountered during annotation. This collaboration ensures that the datasets used for training machine learning models are accurate and comprehensive, directly impacting the success of the project. Expect regular team meetings and ongoing feedback loops to maintain alignment with evolving project requirements.

What is the difference between Machine Learning Data Associate vs Data Analyst?

AspectMachine Learning Data AssociateData Analyst
Required SkillsData cleaning, labeling, basic programming, understanding of ML workflowsData interpretation, visualization, statistical analysis
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, marketing, healthcare sectors
Common CertificationsData Science certifications, Python, SQLExcel, Tableau, SQL certifications

The main difference is that Machine Learning Data Associates focus on preparing and labeling data specifically for machine learning models, while Data Analysts interpret data to generate insights for business decisions. Both roles require strong data skills and often overlap, but their primary objectives and work environments differ.

How do I become a machine learning data associate?

To become a machine learning data associate, candidates typically need a high school diploma or equivalent, with some roles preferring a bachelor's degree in computer science, data science, or related fields. Relevant skills include data annotation, understanding of machine learning concepts, and proficiency with tools like Excel, SQL, or data labeling platforms. Gaining experience through internships or certifications can improve job prospects in this field.

Is a Machine Learning Data Associate a good job?

A Machine Learning Data Associate role involves preparing and managing data for machine learning models, often requiring skills in data cleaning, annotation, and familiarity with tools like Python or SQL. It can be a good entry-level position for those interested in AI and data science, offering opportunities to develop technical skills and gain industry experience. Compensation and job satisfaction vary depending on the employer and location, but it generally provides a solid foundation for a career in machine learning or data analysis.

What cities near Mississauga, ON are hiring for Machine Learning Data Associate jobs?

Cities near Mississauga, ON with the most Machine Learning Data Associate job openings:

Machine Learning Data Associate jobs near you
Infographic showing various Machine Learning Data Associate job openings in Mississauga, ON as of August 2026, with employment types broken down into 1% As Needed, 87% Full Time, 9% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Applied Machine Learning Scientist II

Toronto, ON • On-site

OpenTable
Internet and IT • 1 - 5K employees
Learn more about OpenTableexternal

Full-time

Medical, Dental, Life, Retirement, PTO

Posted 9 days ago

Job description

This hybrid role requires working in the office two days per week.

With millions of diners, 70,000+ restaurant partners and 25+ years of experience, OpenTable, part of Booking Holdings, Inc. (NASDAQ: BKNG), is an industry leader with a passion for helping restaurants thrive. Our world-class technology empowers restaurants to focus on what matters most - their team, their guests, and their bottom line - while enabling diners to discover and book the perfect restaurant for every occasion. 

Every employee at OpenTable has a tangible impact on what we do and how we do it. You'll also be part of a global team and its portfolio of metasearch brands. Hospitality is all about taking care of others, and it defines our culture.

Why this role at OpenTable?

OpenTable seats 25million diners each month across 70000+ restaurants and taps into more than 20years of booking data-an ideal launchpad for an earlycareer ML scientist. In our tightknit team, every experiment you run and every model you ship goes live quickly and at scale. You'll start with wellscoped projects and close mentorship, then rapidly earn the freedom to pitch and implement research ideas that deliver measurable value for diners, restaurants, and the business. We celebrate agency, speed, and relentless experimentation, balanced by disciplined prioritization rooted in ML expertise and realworld production and business constraints. This posting is for an existing vacancy.

Responsibilities

  • Prototype, evaluate, and productionize machine learning systems to enhance restaurant content understanding, retrieval, matching, ranking, and recommendation.
  • Build and monitor scalable data and machine learning pipelines, ensuring strong data quality and reproducibility.
  • Design evaluation frameworks and experiments to define success metrics and continuously improve model quality, relevance, and product impact.
  • Apply large language models (LLMs) and multimodal approaches to content tasks like extraction and classification while optimizing for performance, latency, and cost.
  • Develop reusable machine learning tooling and maintain rigorous standards for code quality, deployment, and documentation.
  • Collaborate cross-functionally with engineering, product, and content teams to translate ambiguous business needs into practical, scalable machine learning solutions.

Minimum Qualifications

  • Bachelor's, Master's, or PhD degree in Computer Science, Statistics, Mathematics, or a related technical field, with 0-3 years of relevant academic or professional experience.
  • Proficiency in Python and foundational machine learning frameworks (e.g., PyTorch, TensorFlow, scikit-learn, XGBoost).
  • Hands-on experience training, tuning, evaluating, and debugging classical machine learning and deep learning models, including Transformers.
  • Strong foundation in software engineering principles, algorithms, and data structures, with familiarity in large-scale data systems.
  • Demonstrated ability to translate business goals into machine learning metrics and address common production issues like data drift and overfitting.

Preferred Qualifications

  • Experience applying machine learning to text, image, or multimodal content for retrieval, matching, ranking, or recommendation.
  • Familiarity with large language model (LLM) workflows for text and image processing tasks.
  • Exposure to search systems, information retrieval, embeddings, or learning-to-rank methodologies.
  • Experience with human-in-the-loop machine learning systems supporting operational or editorial workflows.
  • Demonstrated applied curiosity through substantial technical projects, research, open-source contributions, or internships.

Benefits and Perks

  • Generous paid vacation + time off for your birthday
  • Work from (almost) anywhere for up to 20 days per year
  • Focus on mental health and well-being:
    • Company-paid therapy sessions through SpringHealth
    • Company-paid subscription to Headspace
    • Annual company-wide week off a year - the whole team fully recharges (and returns without a pile-up of work!)
  • Paid parental leave
  • Paid volunteer time
  • Focus on your career growth:
    • Development Dollars
    • Leadership development
    • Access to thousands of on-demand e-learnings
  • Travel Discounts
  • Employee Resource Groups
  • 20 days of paid time off
  • Private health and dental insurance
  • Life and Disability insurance

The best connections happen face-to-face, whether you're sitting down to dinner or having coffee with a coworker. That's why OpenTable has adopted a hybrid workplace model. This role aligns with that approach, with an expectation of coming into the office two days a week-giving employees the best of both worlds: in-person collaboration and flexibility.

The expected range of compensation for this position based in Toronto, Canada, including commission and/or bonuses is $170,000 - $190,000 CAD. There are a variety of factors that go into determining a compensation range, including but not limited to external market benchmark data, geographic location, and years of experience sought/required.

We offer a competitive base salary and benefits including: health benefits; flexible spending account; retirement benefits; life insurance; paid time off (including PTO, paid sick leave, medical leave, bereavement leave, floating holidays and paid holidays); and parental leave benefits. This role is eligible to be considered for an annual bonus and equity grant.

Work Environment & Flexibility

At OpenTable, we pride ourselves on fostering a global and dynamic work environment. As a team member with us, you will benefit from a schedule tailored to accommodate a global workforce operating across multiple time zones. While the majority of your responsibilities may align with conventional business hours, there will be instances where you are expected to manage communications - via calls, Slack messages, or emails - outside of regular working hours to effectively collaborate with international colleagues, respond to restaurant partners, and/or address urgent matters. OpenTable will always abide by and consider local laws and regulations.

Inclusion

We're committed to creating a workplace where everyone feels they belong and can thrive. We know the best ideas come when we bring different voices to the table, so we're building a team as dynamic as the diners and restaurants we serve-and fostering a culture where everyone feels welcome to be themselves.

If you need accommodations during the application or interview process, or on the job, we're here to support you. Please reach out to your recruiter to request any accommodations.

#LI-LR1

#LI-Hybrid

Apply