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Machine Learning Data Associate Jobs in British Columbia

Clio

Machine Learning Engineer

Vancouver, BC · Hybrid

CA$152K - CA$174K/yr

Proficiency in data manipulation, cleaning, and preprocessing for complex unstructured datasets; * Experience with agentic frameworks and workflows * Experience working with open-source LLM ...

Targeted Talent

Data Scientist

New Westminster, BC · On-site

$80K - $100K/yr

Previous experience with Machine Learning, Data Science and solving problems at scale Perks: * Competitive Salary * Individual performance bonus * Health and dental benefits * 3 weeks' vacation

Targeted Talent

Data Scientist

Vancouver, BC · On-site

$80K - $100K/yr

Previous experience with Machine Learning, Data Science and solving problems at scale Perks: * Competitive Salary * Individual performance bonus * Health and dental benefits * 3 weeks' vacation

MetaOptima

Machine Learning Engineer

Vancouver, BC · On-site

$100 - $140/hr

As a Machine Learning Engineer, you will join a small, high-impact R&D team and own the full ML ... Work across all stages of the ML pipeline -- from data cleaning and acquisition through ...

Targeted Talent

Data Scientist

New Westminster, BC

$80K - $100K/yr

Previous experience with Machine Learning, Data Science and solving problems at scale Perks: * Competitive Salary * Individual performance bonus * Health and dental benefits * 3 weeks' vacation

Targeted Talent

Data Scientist

Vancouver, BC · On-site

$80K - $100K/yr

Previous experience with Machine Learning, Data Science and solving problems at scale Perks: * Competitive Salary * Individual performance bonus * Health and dental benefits * 3 weeks' vacation

KPMG

Manager, ML/AI Engineer, Data & AI

Vancouver, BC · On-site

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 ...

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Machine Learning Data Associate information

What are the key skills and qualifications needed to thrive as a Machine Learning Data Associate, and why are they important?

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.

What is the salary for a ML data associate?

The salary for a Machine Learning Data Associate at Amazon typically ranges from $40,000 to $70,000 per year, depending on experience, location, and specific role requirements. Entry-level positions may start lower, while experienced associates or those in higher-cost areas can earn more. Benefits often include health insurance, paid time off, and opportunities for skill development in data annotation and machine learning tools.

What are Machine Learning Data Associates?

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 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.

Is ML 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 depend on the employer, location, and individual career goals.

How much do machine learning data associates make?

Machine Learning Data Associates typically earn between $40,000 and $70,000 annually, depending on experience, location, and the complexity of data tasks. Entry-level positions may start lower, while experienced associates working with large datasets or specialized tools can earn higher salaries.

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 does a machine learning data associate do?

A machine learning data associate is responsible for collecting, cleaning, and organizing data used to train machine learning models. They ensure data quality and consistency, often using tools like SQL, Python, or data annotation platforms, to support accurate model development and deployment.
Machine Learning Data Associate jobs near you
Infographic showing various Machine Learning Data Associate job openings in British Columbia as of July 2026, with employment types broken down into 1% As Needed, 67% Full Time, 30% Part Time, 1% Temporary, and 1% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution.

Machine Learning Engineer

Clio

Vancouver, BC • Hybrid

CA$152K - CA$174K/yr

Full-time

Medical, Dental, Vision

Posted 27 days ago

Job description

Clio is the global leader in legal AI technology, empowering legal professionals and law firms of every size to work smarter, faster, and more securely.

We are transforming the legal experience for all by bettering the lives of legal professionals while increasing access to justice.

Summary:

We are currently seeking a Machine Learning Engineer to join our rapidly growing engineering team. This role is for someone who is passionate about building innovative solutions and being exposed to new challenges and technologies while making an impact.
This role is available to candidates across Canada (excluding Quebec). If you are local to one of our hubs (Burnaby, Calgary, or Toronto) you will be expected to be in office minimum twice per week on one of our Anchor Days.

What your team does:

We at Clio have an amazing team that is on a mission to transform the legal experience for all, and our engineering team's goal is to deliver an incredible experience to our customers.In the AI team in Clio, we use the latest technology in the space of NLP and GenAI to provide our customers with solutions to make their work more streamlined and efficient allowing them to have more time to focus on their clients' needs.

A day in the life might look like:

  • Develop advanced machine learning models using structured and unstructured data to improve Clio's customer's experience

  • Create LLMs based solutions to help Clio's clients to save time and create efficiencies

  • Collaborate cross-functionally with engineering, product management, operations and data science to identify new ML-driven features for Clio customers

  • Work in an agile environment with our team of machine learning engineers, MLOps engineering and full stack developers across a variety of projects

What you may have:

  • Hands-on experience in model development, particularly with traditional machine learning, NLP, and transformer-based models;

  • Proficiency in data manipulation, cleaning, and preprocessing for complex unstructured datasets;

  • Experience with agentic frameworks and workflows

  • Experience working with open-source LLM foundation models and APIs for commercial LLMs, such as ChatGPT or Gemini;

  • A proven ability to quickly learn new technologies and adapt to a dynamic, fast-paced environment with distributed teams and customers;

  • A portfolio of past projects showcasing your successes, challenges, and growth as a machine learning expert;

  • Exceptional communication skills and the ability to build trust with both internal teams and external customers;

  • A strong desire to continuously learn, challenge yourself, and refine your craft as a machine learning engineer.

This posting is for an existing vacancy.

What you will find here:

Compensation is one of the main components of Clio's Total Rewards Program. We have developed a series of programs and processes to ensure we are creating fair and competitive pay practices that form the foundation of our human and high-performing culture.

Some highlights of our Total Rewards program include:

  • Competitive, equitable salary with top-tier health benefits, dental, and vision insurance

  • Hybrid work environment, with expectation for local Clions (Vancouver, Calgary, Toronto, Dublin, London, New York City and Sydney) to be in office min. twice per week.

  • Flexible time off policy, with an encouraged 20 days off per year.

  • $2000 annual counseling benefit

  • RRSP matching and RESP contribution

  • Clioversary recognition program with special acknowledgement at 3, 5, 7, and 10 years

The expected salary range* for this role is $129,200 to $152,000 to $174,800 CAD. There are a separate set of salary bands for other regions based on local currency.


*Our salary bands are designed to reflect the range of skills and experience needed for the position and to allow room for growth at Clio. For experienced individuals, we typically hire at or around the midpoint of the band. The top portion of the salary band is reserved for employees who demonstrate sustained high performance and impact at Clio. Those who are new to the role may join below the midpoint and develop their skills over time. The final offer amount for this role will be dependent on geographical region, applicable experience, and skillset of the candidate.

Diversity, Inclusion, Belonging and Equity (DIBE) & Accessibility

Our team shows up as their authentic selves, and are united by our mission. We are dedicated todiversity, equity and inclusion. We pride ourselves in building and fostering an environment where our teams feel included, valued, and enabled to do the best work of their careers, wherever they choose to log in from. We believe that different perspectives, skills, backgrounds, and experiences result in higher-performing teams and better innovation. We are committed to equal employment and we encourage candidates from all backgrounds to apply.

Clio provides accessibility accommodations during the recruitment process. Should you require any accommodation, please let us know and we will work with you to meet your needs.

Learn more about our culture atclio.com/careers

We're a Human and High Performing AI company, meaning we use artificial intelligence to improve all of our operations. In recruitment, AI helps us streamline the process for greater efficiency. However, we've built our systems to ensure that a human always reviews AI-generated output, and we never make automated hiring decisions.

Disclaimer: We only communicate with candidates through official @clio.com email addresses.

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