Web

Web

ML Data Engineer

Canada - Remote

Sponsorship not specified$100k-$150kDetected 7 days ago
PythonSQLVector DatabasesAWSGCPMachine LearningData EngineeringRAGMLOps

About the role

  • Individual salaries are determined by various factors including, but not limited to candidate qualifications such as skills, education, and experience, as well as internal equity and market conditions

Responsibilities

  • Developing API-based ingestion frameworks, event-streaming solutions, real-time and batch data pipelines, and optimizing large-scale data processing environments.
  • Supports emerging AI technologies such as embeddings, vector databases, retrieval-augmented generation (RAG), and AI-driven application integration.
  • Partners closely with data engineering, BI, analytics, application, and AI teams to ensure enterprise data is reliable, governed, scalable, and optimized for both reporting and AI-driven use cases.

Requirements

  • Strong experience with cloud data platforms, distributed data processing, SQL and Python development, and modern data architecture patterns.
  • Experience with OCI, AWS, or GCP environments, as well as exposure to AI/ML operationalization and MLOps concepts, is highly desirable.

Compensation

  • The target compensation range for this position is $100k - $150k CAD annually.

Company info

  • Newfold Digital is a leading web technology company serving millions of customers globally.
  • Our customers know us through our robust portfolio of brands.
  • We have some of the industry's most prominent and storied go-to-market brands, including Bluehost, HostGator, Domain.com, Network Solutions, Register.com and Web.com.
  • We help customers of all sizes build a digital presence that delivers results.
  • With our extensive product offerings and personalized support, we take pride in collaborating with our customers to serve their online presence needs.
  • The strength of our company lives in the intersection of our people, our customers, and our brands.

This listing is sourced directly from Web's careers page and normalized into a canonical job model.