Machine Learning Engineer

Posted 10 Days Ago
Be an Early Applicant
2 Locations
Junior
Fintech • Consulting
The Role
The Machine Learning Engineer will manage the lifecycle of models, develop APIs, maintain documentation, and support data-related inquiries. Responsibilities include data pipeline management and ensuring compliance with industry standards.
Summary Generated by Built In

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


Primary Location:

AUS-MelbourneAUS-Sydney-Blue-Street

Function:

Function - Data and Analytics

Schedule:

Full time

Top Skills

Git
Google Cloud Platform
Python
SQL
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The Company
HQ: Atlanta, GA
16,742 Employees
On-site Workplace

What We Do

At Equifax (NYSE: EFX), we believe knowledge drives progress. As a global data, analytics, and technology company, we play an essential role in the global economy by helping financial institutions, companies, employers, and government agencies make critical decisions with greater confidence. Our unique blend of differentiated data, analytics, and cloud technology drives insights to power decisions to move people forward.

Headquartered in Atlanta and supported by nearly 15,000 employees worldwide, Equifax operates or has investments in 24 countries in North America, Central and South America, Europe, and the Asia Pacific region.

For more information, visit Equifax.com.

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