Machine Learning Engineer

Work Location - Sydney/ Melbourne

This role is required to maintain the lifecycle of models developed by the Data Science chapter and develop APIs/systems on top of these models. Machine Learning Engineer (MLE) will deploy models across various platforms (A2P/GME, and batch) as needed, manage end-to-end pipelines, logs, and address queries and issues.

What you’ll do

Manage project progress, metadata collection, and data development with minimal supervision, ensuring timely and accurate delivery.
Maintain and organize information within documentation repositories.
Conduct investigations into internal and external stakeholder queries, operating under the guidance of the Team Leader.
Analyze problems, identify root causes, and formulate clear findings and observations.
Propose effective resolutions and communicate results to stakeholders, with moderate guidance.
Maintain up-to-date knowledge of industry regulatory requirements, including reporting mandates and compliance standards.
Provide support for internal and external inquiries related to data standards.
Perform intermediate-level data quality checks, adhering to established procedures.
Follow established security protocols to protect sensitive data.
Identify and report potential security vulnerabilities.

What Experience You Need

Bachelor's degree in STEM or related field (Master's preferred).
2+ years of data engineering or related experience.
Proficiency in Python, SQL, or scripting languages (intermediate level).
Basic understanding of Google Cloud Platform (GCP) and cloud computing.
Experience building and maintaining basic data pipelines.
Experience supporting data model design and implementation.
Proficient Git usage and contribution to team repositories.
Cloud certification (strongly preferred)

What could set you apart

GCP and extensive Python experience
Interest in and experience in Data and Data Science, modelling, and AI

What’s in it for you?

At Equifax, we are on a mission to ensure that you have the support, resources and opportunities to Power Your Possible. Here are just a few ways we give back to our teams:

Hybrid Work Model
Additional Leave Allocations + Public Holiday Swaps
Discounted Gym Memberships
Discounted Private Health Cover (and discounted Pet Insurance if you want it!)
Employee Stock Purchase Plan
Career Development and Learning
A Diverse and Inclusive Workplace and Environment
Wellbeing Resources

Machine Learning Engineer

Key Skills

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