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AI Platform Engineer

Compass Group Canada

Toronto · Hybrid Full-time Senior CA$110k – CA$150k/yr Today

About the role

About

At Compass Data & AI (CDAI), our mission is to create extraordinary experiences at the intersection of hospitality and technology. The CDAI AI Platform Engineering team is seeking an experienced and highly skilled AI platform engineer to lead the development of cutting‑edge AI/ML infrastructure that helps our partners make smarter business decisions.

Responsibilities

  • Build robust, reliable infrastructure that enables and accelerates AI applications and services deployed across the company.
  • Collaborate with cross‑functional teams to identify business needs and develop innovative data‑driven solutions that drive measurable impact.
  • Provide guidance and feedback on infrastructure and system architectures that power AI‑driven decision making.
  • Design and implement robust data infrastructure, following governance practices around data integrity and security.
  • Mentor and guide data scientists, fostering a collaborative environment for knowledge sharing and skill development.
  • Stay updated with industry trends, emerging technologies, and best practices in machine learning, AI, LLMs, and data science.

Requirements

  • 5 years of hands‑on experience building and deploying machine learning and AI pipelines in a commercial environment.
  • Experience with cloud‑based data platforms (AWS, GCP, Snowflake preferred) and related services (Airflow, SageMaker, Vertex AI).
  • Expert in writing Python, Terraform, and familiarity with Golang.
  • Proven track record of delivering successful data‑driven solutions that have produced tangible business outcomes.
  • Skilled in automating processes with GitHub Actions pipelines.
  • Excellent communication and interpersonal skills, with the ability to collaborate effectively with cross‑functional teams and convey complex technical concepts to non‑technical stakeholders.

Preferred Qualifications

  • 3 + years of experience working in infrastructure and platform engineering teams.
  • Experience with clustering algorithms and recommender systems.
  • Knowledge of software engineering practices and version control systems.
  • Minimum Bachelor’s degree in STEM or a related field (required).
  • Master’s or Ph.D. in STEM or a related field (preferred).

Position Details

  • Title: AI Platform Engineer
  • Salary Range: $110,000 – $150,000
  • Perks: Bonus, 4 weeks vacation, RRSP, benefits, and more
  • Employment Type: Full‑time, permanent
  • Work Arrangement: Hybrid – 3 days a week in Toronto/Mississauga

Compensation is provided in accordance with provincial legislation and transparent hiring practices. Final compensation will be determined based on qualifications, experience, and internal equity. Canadian work experience is not required. Artificial intelligence tools are utilized in the applicant screening process.

Requirements

  • 5 years of hands-on experience in building and deploying machine learning and AI pipelines in a commercial environment.
  • Experience with cloud-based data platforms (AWS, GCP, Snowflake preferred) and related services (Airflow, Sagemaker, Vertex AI).
  • Expert in writing Python, Terraform, and familiarity with Golang.
  • Proven track record of delivering successful data-driven solutions that have driven tangible business outcomes.
  • Skilled in automating processes with GitHub Actions pipelines.
  • Excellent communication and interpersonal skills, with the ability to effectively collaborate with cross-functional teams and communicate complex technical concepts to non-technical stakeholders.

Responsibilities

  • Build robust, and reliable infrastructure that enables and accelerates AI applications and services that are deployed at the company.
  • Collaborate with cross-functional teams to identify business needs and develop innovative data-driven solutions that drive measurable impact.
  • Provide guidance and feedback on infrastructure and system architectures that power AI driven decision making.
  • Design and implement robust data infrastructure, following governance practices around data integrity and security.
  • Mentor and provide guidance to data scientists, fostering a collaborative environment for knowledge sharing and skill development.
  • Stay updated with industry trends, emerging technologies, and best practices in machine learning, AI, LLMs, and data science.

Benefits

BonusVacationRRSPBenefits

Skills

AirflowAWSGCPGitHub ActionsGolangLLMsMachine LearningPythonSagemakerSnowflakeTerraformVertex AI

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