Senior ML Engineer – MLOps & Mechanistic Interpretability

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

Benefits offered by this job

4 days in-office collaboration (Mon-TH

Friday Flexibility

Job summary

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

You will bridge Mechanistic Interpretability (XAI) research with production workflows, designing systems that map latent embeddings to human-readable credit concepts and serving models at scale with transparency and regulatory defensibility.

Qualifications

• BS degree in a STEM field; Master’s degree preferred.
• 7+ years of related work experience with leadership of ML/DS/DevOps or related teams.
• Experience end-to-end development of ML models with scalability and reliability.

Responsibilities

• Design complex systems for training and running machine learning models with industry best practices.
• Define projects and scope for teams of engineers and guide their completion.
• Develop, identify, and report IP through patent applications, disclosures, white papers, and presentations.
• Communicate effectively with executives, customers, and cross-functional teams.
• Contribute to all phases of product development from analysis to deployment.
• Deliver on company initiatives and align projects with technical vision.
• Collaborate with product, architects, and data teams to leverage AI, ML, and data engineering.
• Participate in peer design and code reviews.
• Drive improvements and innovations to advance the IT organization.
• Mentor and elevate colleagues; may lead a team.

Skills

Machine learning

Team leadership

MLOps

Regulatory compliance

Interpretability

Education

Bachelor's in STEM

Master’s degree preferred

Tools

Python

TensorFlow/PyTorch

Job description

We are seeking a Senior ML Engineer to build the MLOps foundation and interpretability framework for our next-generation credit risk engines. Your mission is two-fold: create the infrastructure for scalable Transformer-based model deployment, and build the "glass box" tooling that transforms model internals into regulatory-compliant, human-understandable insights.

You will bridge the gap between cutting-edge Mechanistic Interpretability (XAI) research and high-stakes financial production workflows. You will design the systems that map latent embeddings to human-readable credit concepts, build the MLOps pipelines to serve these models at scale, and ensure our AI engines are not just high-performing, but transparent, defensible, and ready for global regulatory scrutiny.

We believe great things happen when teams connect. Our schedule is built around 4 days of high-impact, in-office collaboration (Monday-Thursday) , paired with Friday Flexibility to wrap up your week remotely.

This role reports to our office Alpharetta, GA office.

This position does not offer immigration sponsorship (current or future) including F-1 STEM OPT extension support.

This is a direct-hire role and is not open to C2C or vendors.

What you’ll do

• Design complex systems of systems for training and running machine learning models with industry best practice
• Define projects and scope for teams of engineers and guide their completion
• Develop, identify, and report intellectual property through patent applications, invention disclosures, white papers, and presentations
• Demonstrate effective, respectful, and honest communication when collaborating with colleagues including executives, customers, and peers from other businesses and institutions
• Contribute to all phases of product development and delivery from Analysis & Design all the way through to successful Deployment
• Deliver on company initiatives and prioritize projects supporting your long term technical vision
• Collaborate with the product team, architects, and others to understand the opportunities and limitations of AI, ML, and data engineering
• Participate in peer design and code reviews
• Show initiative to identify and drive forward improvements and innovations that add value and move the IT organization forward
• Elevate the performance of colleagues through training, mentoring, and promoting best practices; may function as a team lead

What experience you need

• BS degree in a STEM major or equivalent job experience required; Master’s Degree preferred; AI/ML coursework preferred
• 7+ years of related work experience, including proven experience leading a team of MLE, DS, SDE, DevOps, or related roles
• Experience with end-to-end development of ML models, from ideation to deployment, ensuring best practices, scalability and reliability

What could set you apart

• Application Development/Programming - Ability to review code for quality, performance, and efficiency, and optimize critical parts of the codebase; Ability to establish the best practices of Software Development Life Cycle for the team
• Artificial Intelligence - Designing scalable and maintainable machine learning architectures and frameworks for the organization's products and services; Ability to define the technical vision and roadmap for the MLE team aligned with the organization's goals and industry trends
• Big Data Analytics - Deep understanding of the domain or industry in which the machine learning solutions are being applied, enabling the company to develop impactful big data solutions
• Cloud Computing - Proficiency in data architecture design, data strategy development, data orchestration, data integration, ETL development, data modeling, parallel processing and performance optimization.
• Collaboration - Being able to engage with internal stakeholders, including data scientists, business leaders, product managers, and executives, to understand requirements and present technical solutions; Ability to collaborate with other teams, such as software engineering, data engineering, and business intelligence, to integrate machine learning solutions into larger systems.
• Mathematics - Ability to read and comprehend research papers in latest machine learning field, and applying innovative techniques to real-world problems
• Technical Leadership - Be able to lead and manage a team of machine learning engineers, data scientists, or related roles. Ability to set clear goals, provide guidance, and foster a collaborative and productive team environment
• Cloud Certification Strongly Preferred