Senior ML Engineer - MLOps & Glassbox Interpretability

Equifax, Inc. in; Alpharetta (GA); Hybrid; USD 140,000 - 210,000; Full time

Job summary

Equifax, Inc. in Alpharetta, GA is seeking a Senior ML Engineer to build the MLOps foundation and interpretability framework for our next-generation credit risk engines.

You will design scalable Transformer-based deployment and glass-box tooling for regulatory-compliant insights. The role bridges XAI research with production workflows, mapping latent embeddings to human-readable credit concepts while ensuring AI systems are high-performing, transparent, and ready for global regulatory scrutiny.

Qualifications

• BS degree in a STEM field or equivalent experience required.
• Master's degree preferred; AI/ML coursework recommended.
• Experience leading ML/DS/DevOps teams and projects.

Responsibilities

• Design complex systems of systems for training and running ML models with best practices.
• Define projects and scope for teams of engineers and guide completion.
• Develop and report IP through patent apps, disclosures, white papers, and presentations.
• Communicate effectively with executives, customers, and peers across domains.
• Contribute to all phases of product development from analysis to deployment.
• Deliver initiatives and prioritize projects aligned with the technical vision.
• Collaborate with product, architects, and data teams to leverage AI and data engineering.
• Participate in peer design and code reviews.
• Identify and drive improvements that add value and move IT forward.
• Mentor colleagues and promote best practices; may lead a team.

Skills

ML engineering

MLOps

Team leadership

End-to-end ML

Education

BS degree in STEM

Master's degree preferred

AI/ML coursework preferred

Job description

Equifax, Inc. in Alpharetta, GA is seeking a Senior ML Engineer to build the MLOps foundation and interpretability framework for our next-generation credit risk engines.

You will design scalable Transformer-based deployment and glass-box tooling for regulatory-compliant insights. The role bridges XAI research with production workflows, mapping latent embeddings to human-readable credit concepts while ensuring AI systems are high-performing, transparent, and ready for global regulatory scrutiny.