Machine Learning Engineer

About the role

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

Responsibilities

• Solve challenging technology problems and build architecturally sound, high-quality software that moves data through models to make automated decisions.
• Communicate, collaborate, and develop creative and performant solutions to help Equifax provide certainty in every digital transaction for our customers.
• Work with data scientists to develop requirements for novel algorithms, and with operations and other developers to bring data transformation pipelines and machine learning models to practice.
• Design platforms and pipelines for researching, developing, and running machine learning models.
• Productionize machine learning models by building performant data transformations, storage, and pipelines.
• Develop and maintain microservices that serve data, model features, and scores to other internal services, as well as external customers.
• Demonstrate effective, respectful, and honest communication when collaborating with colleagues including a cross-functional team consisting of Data Science, Operations, and Engineering.
• Apply development and testing best practices (including unit, service, and integration tests) and demonstrate excellent 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.
• Deliver on company initiatives and projects prioritized for your team and support long term technical vision.
• Collaborate with the product team, architects, and others to document features and changes.
• Identify gaps and iterative improvements to legacy model platforms, frameworks, or governance stacks.
• Adhere to and influence best practices (i.e. security, architecture, platform, etc.).
• Participate in peer design and code reviews.
• Participate in on-call rotation with other engineers.

Requirements

• BS in Computer Science, Engineering, or equivalent experience.
• 3+ years of strong software engineering and software architecture background using languages such as Golang, Python, and SQL.
• 3+ years of experience building RESTful APIs and/or gRPC within a distributed microservice architecture.
• 2+ years of experience implementing Amazon Web Services (e.g., IAM, Lambda, EKS, Neptune, DynamoDB, RDS).
• 2+ years of experience using IaC tooling such as Terraform.
• Experience working with machine learning frameworks such as SparkMLlib, Scikit-Learn, MLflow, or TensorFlow.
• Experience serving ML model inference at scale in low-latency.
• Experience with metrics, logging, and evaluating model performance (e.g., DataDog, evaluation latency, and ROC curves).

Qualifications

• Experience with Snowflake.
• Experience with AWS EMR.
• Experience deploying diverse model architectures into production using portable formats like ONNX or MLeap.