End-to-End AI Architect for Enterprise Impact in Toronto

End-to-End AI Architect for Enterprise Impact in Toronto

Toronto Full-Time 121500 - 148500 $ / year (est.) On-site
V

At a Glance

  • Tasks: Own the full AI lifecycle, from data ingestion to model deployment.
  • Company: Virtusa, a leading tech company in Toronto focused on AI innovation.
  • Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
  • Other info: Join a dynamic team with a focus on innovation and career advancement.
  • Why this job: Make a real impact by integrating AI into enterprise systems and ensuring quality solutions.
  • Qualifications: Experience in AI/ML, data pipelines, and strong problem-solving skills.

The predicted salary is between 121500 - 148500 $ per year.

Virtusa in Toronto is seeking an AI/ML specialist to own the full AI lifecycle—from data ingestion and preparation to model training, evaluation and production deployment. You’ll engineer data pipelines and APIs to integrate AI into enterprise systems while ensuring secure, scalable, and governance-compliant solutions.

You will build automated evaluation loops for model quality and bias, quantify ROI, and embed transparency, audit trails, and data lineage in every solution, partnering with risk.

End-to-End AI Architect for Enterprise Impact in Toronto employer: Virtusa

Kinetica is an exceptional employer that fosters a collaborative and innovative work culture, where your expertise in data modeling and analytics will be valued and utilized to drive impactful solutions. Located in a vibrant tech hub, Kinetica offers competitive benefits, opportunities for professional growth, and the chance to work with cutting-edge technology in an Agile environment, making it an ideal place for those seeking meaningful and rewarding employment.

V

Contact Details:

Virtusa Recruitment Team

We think you need these skills to ace End-to-End AI Architect for Enterprise Impact in Toronto

AI/ML Expertise
Data Ingestion
Data Preparation
Model Training
Model Evaluation
Production Deployment
Data Pipeline Engineering