Time since we first saw it
Day 67
Similar jobs usually come down between day 8 and day 76.
At Aviva, jobs usually come down by about day 51.
From 5,517 similar postings that came down, and 15 of Aviva’s. Coming down is not always a hire.
What you’ll get: The salary band for this position ranges from $90,000 to $115,000. Please note that individual salary is determined by factors such as job-related knowledge, skills and experience, as well as internal equity. Compelling rewards package including base compensation, eligibility for annual bonus, retirement savings, share plan, health benefits, personal wellness, and volunteer opportunities.Read the full posting
Design and implement ML pipelines and services in cloud and on-premise setups
Support model deployment, monitoring and performance optimization
Apply MLOps practices like CI/CD, model versioning and retraining workflows
Work with Snowflake and AWS services to support ML model deployment
Ensure data privacy, security and compliance standards are met
Assist in designing and implementing ML pipelines and services in cloud and on-premise environments.
Support model deployment, monitoring, and performance optimization.
Apply MLOps practices such as CI/CD, model versioning, and retraining workflows.
Work with Snowflake and AWS services to support ML model deployment.
Ensure adherence to data privacy, security, and compliance standards.
What you’ll bring: - Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field. - 2–4 years of experience in machine learning engineering or related roles.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.
Day 67
Similar jobs usually come down between day 8 and day 76.
At Aviva, jobs usually come down by about day 51.
From 5,517 similar postings that came down, and 15 of Aviva’s. Coming down is not always a hire.
14 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- 2–4 years of experience in machine learning engineering or related roles. - Proficiency in Python, along with data processing and ML libraries (e.g., Pandas, NumPy, scikit-learn, XGBoost). - Familiarity with AWS and/or Snowflake cloud services, as well as Linux-based systems.
- Basic experience with Jenkins and containerization tools such as Docker. - Strong SQL skills, including an understanding of query optimization techniques. - Exposure to ML workflow tools (e.g., MLflow, Airflow) and monitoring frameworks is a plus.
- Apply MLOps practices such as CI/CD, model versioning, and retraining workflows. - Work with Snowflake and AWS services to support ML model deployment. - Contribute to the development and maintenance of on-premise ML workflows.
- Proficiency in Python, along with data processing and ML libraries (e.g., Pandas, NumPy, scikit-learn, XGBoost). - Familiarity with AWS and/or Snowflake cloud services, as well as Linux-based systems. - Basic experience with Jenkins and containerization tools such as Docker.
- Experience with Apache Spark and Snowpark for scalable data processing. - Exposure to cloud platforms (e.g., AWS, Snowflake, Azure, GCP). What you’ll get:
- Familiarity with AWS and/or Snowflake cloud services, as well as Linux-based systems. - Basic experience with Jenkins and containerization tools such as Docker. - Strong SQL skills, including an understanding of query optimization techniques.
- Strong SQL skills, including an understanding of query optimization techniques. - Exposure to ML workflow tools (e.g., MLflow, Airflow) and monitoring frameworks is a plus. - Strong analytical and problem-solving abilities.
What makes you stand out: - Experience with Apache Spark and Snowpark for scalable data processing. - Exposure to cloud platforms (e.g., AWS, Snowflake, Azure, GCP).
Complete your application on aviva.wd1.myworkdayjobs.com. The employer’s form will show what is required.
Already applied? Track this application
Yes. We’ve followed one other Intermediate Machine Learning Engineer job there since May 2026. It came down after 75 days.
New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Together, we are Aviva. Our values — Care, Commitment, Community, and Confidence — guide how we show up for each other and for our customers. Individually, they’re words. Together, they define who we are.
At Aviva Canada, we put people first, our employees, our customers, and our communities. We’re proud of a culture built on care, inclusion, and collaboration, where your voice matters and your growth is supported. We’re not just about insurance; we’re about making a real difference by protecting what matters most.
The OpportunityWe are looking for a talented and motivated Intermediate Machine Learning Engineer to join our AI/ML Operations & Platform team. The ideal candidate will have hands-on experience in building and deploying machine learning solutions, with an understanding of cloud technologies and data platforms. You will work closely with ML engineers, data scientists, and product teams to support the development and operationalization of ML models across the organization.
What you’ll do:Assist in designing and implementing ML pipelines and services in cloud and on-premise environments.
Collaborate with cross-functional teams to gather requirements and contribute to scalable ML solutions.
Support model deployment, monitoring, and performance optimization.
Apply MLOps practices such as CI/CD, model versioning, and retraining workflows.
Work with Snowflake and AWS services to support ML model deployment.
Contribute to the development and maintenance of on-premise ML workflows.
Ensure adherence to data privacy, security, and compliance standards.
Participate in code reviews and knowledge sharing within the team.
Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field.
2–4 years of experience in machine learning engineering or related roles.
Proficiency in Python, along with data processing and ML libraries (e.g., Pandas, NumPy, scikit-learn, XGBoost).
Familiarity with AWS and/or Snowflake cloud services, as well as Linux-based systems.
Basic experience with Jenkins and containerization tools such as Docker.
Strong SQL skills, including an understanding of query optimization techniques.
Exposure to ML workflow tools (e.g., MLflow, Airflow) and monitoring frameworks is a plus.
Strong analytical and problem-solving abilities.
Experience with Apache Spark and Snowpark for scalable data processing.
Exposure to cloud platforms (e.g., AWS, Snowflake, Azure, GCP).
The salary band for this position ranges from $90,000 to $115,000. Please note that individual salary is determined by factors such as job-related knowledge, skills and experience, as well as internal equity.
Compelling rewards package including base compensation, eligibility for annual bonus, retirement savings, share plan, health benefits, personal wellness, and volunteer opportunities.
Hybrid flexible work model.
Outstanding career development opportunities.
We’ll support your professional development education.
Competitive vacation package with the option to purchase 5 extra days off per year.
Employee-driven programs focused on gender, LGBTQ+, origins, diversity, and inclusion.
Corporate wellness programs to support our employees’ physical and mental health.
Employee discount on home and auto insurance (where applicable).
This job advertisement is for an existing vacancy which has been posted both internally & externally.
Aviva Canada may use AI (Artificial Intelligence) tools to assist us throughout the recruitment process to screen, assess or select applicants for a position.
Aviva Canada has an accommodation process in place to provide accommodations for employees with disabilities. If upon commencement of employment you require a specific accommodation because of a disability, please contact your Talent Acquisition Partner so that an appropriate accommodation can be arranged. This process applies throughout your career with Aviva Canada.
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What you’ll get: The salary band for this position ranges from $90,000 to $115,000. Please note that individual salary is determined by factors such as job-related knowledge, skills and experience, as well as internal equity. Compelling rewards package including base compensation, eligibility for annual bonus, retirement savings, share plan, health benefits, personal wellness, and volunteer opportunities.
Markham
- Compelling rewards package including base compensation, eligibility for annual bonus, retirement savings, share plan, health benefits, personal wellness, and volunteer opportunities. - Hybrid flexible work model. - Outstanding career development opportunities.
#LI-MH1 #LI-Hybrid
No clear work-authorization passage found. Eligibility is unconfirmed.