Who we are.
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.
Role Summary:
The ML Data Engineer is responsible for designing, developing, and supporting scalable data and AI platforms that enable machine learning, advanced analytics, and intelligent applications across the enterprise. This role focuses on building robust data pipelines, integrating structured and unstructured data sources, and supporting AI/ML solutions in cloud-based environments.
What you'll do and how you'll make your mark:
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.
Who you are and what you'll need to succeed:
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.
The target compensation range for this position is $100k - $150k CAD annually. 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
