Machine Learning Engineer - Remote Opportunity

About the Role

Equifax is seeking a Machine Learning Engineer to join our Data and Analytics Center of Excellence (D&A COE). In this remote role, you will serve as the critical engineering bridge between advanced AI research and robust, scalable model development. Your primary mandate is to accelerate our R&D lifecycle by engineering high-performance training pipelines and unlocking model portability across the organization.

What You'll Do

• Design and build high-throughput data pipelines (e.g., BigQuery to TFRecords) specifically engineered for distributed training and inference.
• Partner with applied data scientists to translate complex prototypes into clean, modular, and scalable production-ready code.
• Productionize machine learning models by building performant data transformations, storage, and pipelines.
• Apply development and testing best practices and demonstrate skilled software craftsmanship to produce maintainable, scalable, and quality solutions.
• Contribute to all phases of product development and delivery from Analysis & Design all the way through to successful Deployment.
• Stay current on state-of-the-art deep learning architecture and training paradigms.
• Demonstrate effective, respectful, and honest communication when collaborating with colleagues including a cross-functional team consisting of QA, Operations, and other team members.
• Deliver on company initiatives and projects prioritized for your team and support long-term technical vision.

Requirements

• BS degree in a STEM major or equivalent job experience required; Master’s Degree preferred; AI/ML coursework preferred.
• 2-5 years of related experience in machine learning engineering.
• Proficiency in Python and experience with data processing and machine learning libraries (Pandas, Numpy, Scipy, Sklearn, Tensorflow, Pytorch, etc.).
• Experience with ML models design, development, or deployment.
• Experience with cloud platforms and distributed computing frameworks.
• Experience writing complex SQL queries and building large-scale data transformation pipelines to feed machine learning workflows.
• Experience architecting deep learning systems (TensorFlow ecosystem preferred), including custom data loading pipelines (e.g., tf.data, TFRecord serialization).
• Cloud Certification Strongly Preferred.

Nice to Have

• Advanced Framework Knowledge - Experience with deep learning framework (e.g. Tensorflow, Jax) internals, including custom training loops, subclassed Keras layers (e.g., custom attention mechanisms), and distributed training strategies (e.g., via tf.distribute).
• Large-Scale Distributed AI - Experience scaling models for distributed training and inference across multi-GPU clusters utilizing data, model, and/or tensor parallelism.
• Domain Expertise - Background in building models utilizing financial, credit, or complex time-series data.
• Cloud Computing - Understand big data processing frameworks and various database technologies.
• Mathematics - Understand advanced statistical concepts and machine learning algorithms.
• Collaboration - Excellent verbal and written communication skills to document and present findings clearly.
• Technical Leadership - Demonstrates an ability to provide guidance to colleagues.

What We Offer

• Competitive salary in the range of $120,000 to $150,000 annually.
• Visa sponsorship available for qualified candidates.
• Hybrid work schedule with flexibility for remote work.
• Opportunities for professional development and growth.
• Collaborative and innovative work environment.