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Aviva

Intermediate Machine Learning Engineer

Aviva is hiring an Intermediate Machine Learning Engineer. It pays $90k-$115k a year and Level rates it ; you can apply on Aviva.

Level's read on this job

  • Builds AI ●●●● is how Level rates this machine learning engineer role: the job is building AI systems.
  • The posting mentions scikit-learn, XGBoost and MLflow among its tools and skills.
  • Level classes it as a mid-level role.
  • Aviva has 140 other open roles on Level.

AI in this role

Intermediate machine learning engineer building, deploying, and operationalizing ML pipelines and models in cloud environments.

scikit-learnXGBoostMLflowPythonpandasNumpyAWSSnowflakeLinuxJenkinsDockerSQL+3
ml-opsmachine-learningmlopscloud-computingci-cddata-engineering
Experience Aviva

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 Opportunity

We 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.

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.

  • 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.

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).

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.

  • 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.

#LI-MH1

#LI-Hybrid

How we rate this

Intermediate Machine Learning Engineer at Aviva rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

ML OpsMachine learningMLOpsCloud ComputingCI/CDData Engineeringscikit-learnXGBoost

Also common in machine learning engineer jobs at this level

Pay

This job starts at
$90k
Typical machine learning engineer job
$199k

This posting starts 55% below the typical machine learning engineer job. See machine learning engineer jobs

Questions you could be asked

  1. How do you monitor a model once it's live, and how do you know it needs retraining?
  2. Tell me about a project where machine learning was part of your work. What did you do?
  3. Tell me about a project where mlops was part of your work. What did you do?
  4. Tell me about a project where cloud computing was part of your work. What did you do?
  5. Tell me about a project where ci/cd was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: ML Ops, Machine learning, MLOps, Cloud Computing, and CI/CD. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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