Machine Learning Engineer

We are seeking a skilled Machine Learning Engineer to join our dynamic team at Equifax Workforce Solutions. The ideal candidate will have a strong background in machine learning, data science and software engineering. Responsibilities include contributing to all phases of product development and delivery from analysis through successful deployment.

The Machine Learning Engineer will work a hybrid schedule, requiring 3 days in the office, from either our St Louis or Atlanta locations.

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
• 2+ years of related work experience, including proven experience leading a team of MLE, DS, SDE, DevOps, or related roles
• 5+ Experience with end-to-end development of ML models, from ideation to deployment, ensuring best practices, scalability and reliability

What could set you apart:

• Cloud Certification Strongly Preferred

• Machine learning implementation and project experience using cloud platforms (Google Cloud Platform, Amazon Web Services, Microsoft Azure, etc.)

• Experience implementing MLOps and the automated training/deployment/monitoring of models in production systems.

• Google Cloud Platform experience strongly preferred

• Experience using GCP's ML/AI suite of tools, especially Gemini, Vertex AI Platform & Notebooks, Vision AI, Document AI, and BigQuery ML.

• A natural curiosity for domain knowledge of business practices the AI/ML project is trying to solve

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