Senior Software/ML Engineer (Finance)

Equifax is seeking creative, high-energy and driven software engineers with hands-on development skills to work on a variety of meaningful projects. Our software engineering positions provide you the opportunity to join a team of talented engineers working with leading-edge technology. You are ideal for this position if you are a forward-thinking, committed, and enthusiastic software engineer who is passionate about technology.

This role requires being in the office 3 days/week on Tues - Thurs.

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

What you'll do

• Demonstrate a deep understanding of cloud native, distributed micro service based architectures
• Deliver solutions for complex business problems through software standard SDLC
• Build strong relationships with both internal and external stakeholders including product, business and sales partners
• Demonstrate excellent communication skills with the ability to both simplify complex problems and also dive deeper if needed
• Build and manage strong technical teams that deliver complex software solutions that scale
• Manage teams with cross functional skills that include software, quality, reliability engineers, project managers and scrum masters
• Provide deep troubleshooting skills with the ability to lead and solve production and customer issues under pressure
• Leverage strong experience in full stack software development and public cloud like GCP and AWS
• Mentor, coach and develop junior and senior software, quality and reliability engineers
• Lead with a data/metrics driven mindset with a maniacal focus towards optimizing and creating efficient solutions
• Ensure compliance with EFX secure software development guidelines and best practices and responsible for meeting and maintaining QE, DevSec, and FinOps KPIs
• Define, maintain and report SLA, SLO, SLIs meeting EFX engineering standards in partnership with the product, engineering and architecture teams
• Collaborate with architects, SRE leads and other technical leadership on strategic technical direction, guidelines, and best practices
• Drive up-to-date technical documentation including support, end user documentation and run books
• Lead Sprint planning, Sprint Retrospectives, and other team activity
• Responsible for implementation architecture decision making associated with Product features/stories, refactoring work, and EOSL decisions
• Create and deliver technical presentations to internal and external technical and non-technical stakeholders communicating with clarity and precision, and present complex information in a concise format that is audience appropriate

What experience you need

• Bachelor's degree or equivalent experience; a Master's Degree is preferred, especially with AI/ML coursework.
• 7+ years of software engineering experience, with a proven track record of writing, debugging, and troubleshooting code with high proficiency in Python. Experience with Django, TypeScript/JavaScript, HTML, and CSS is also valuable.
• 7+ years of experience with Cloud technology, specifically GCP and AWS.
• 7+ years of experience designing and developing cloud-native solutions and microservices using Python, GCP SDKs, and GKE/Kubernetes.
• 3+ years of experience with end-to-end development of ML models, from ideation to deployment, ensuring best practices, scalability, and reliability.
• Demonstrable experience working programmatically with various Data Engineering tool APIs in cloud environments, including:
  
  • Google Cloud Platform (GCP): Dataflow, Composer, BigQuery, Pub/Sub, Vertex AI
• Amazon Web Services (AWS): Glue, Kinesis, Redshift

What could set you apart

• You're a self-starter who can identify and respond to priority shifts with minimal supervision.
• You possess strong communication and presentation skills.
• You demonstrate strong leadership qualities, along with proven problem-solving skills and the ability to mentor and guide individuals to increase their skills.
• Strong expertise in Generative AI (GenAI), including:
  
  • A natural curiosity for domain knowledge of the business practices the AI/ML project is trying to solve.
  • Experience with popular GenAI models such as Gemini, ChatGPT, GROK, Claude, Llama, etc.
  • Experience using GenAI to accelerate development, generating documentation, and processing complex data for analysis
  • Experience creating and deploying AI agents to production environments.
  • Proven ability to develop multi-agent workflow-based, self-reflective, RAG, reactive, and tools agents.
  • A strong understanding of security in AI and responsible AI practices.
  • Strong familiarity with MLOps principles and practices, including automated training, deployment, and monitoring of models in production.
• Hands-on experience with Cloud ML/AI suite of tools
  
  • Google Cloud Platform (GCP): Gemini, Vertex AI Platform & Notebooks, Vision AI, Document AI, and BigQuery ML.
• Cloud Certification strongly preferred, particularly Google Cloud Platform (e.g., Professional Machine Learning Engineer, Professional Data Engineer) or AWS (e.g., Machine Learning Specialty, Data Analytics Specialty).
• Experience creating and maintaining product and software roadmaps.
• Experience working in a highly regulated environment.
• Experience working in Agile environments (e.g., Scrum, XP).
• Familiarity with relational databases such as PostgreSQL and SQL Server.
• Experience with Atlassian tooling (e.g., JIRA, Confluence, and GitHub).
• Proficiency with source code control management systems (e.g., SVN/Git, GitHub) and build tools like Maven & Gradle.

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