Senior ML Engineer — Production AI & Pipelines

Q2

Austin (TX)

Hybrid

USD 140,000 - 190,000

Full time

3 days ago
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Benefits offered by this job

Hybrid Work Opportunities
Flexible Time Off
Career Development & Mentoring
Health & Wellness Benefits
Parental Leave
Volunteer Programs
You Earned it

Job summary

Q2 is a leading provider of digital banking and lending solutions to banks, credit unions, and fintechs in the U.S. and internationally.

As a Machine Learning Engineer, you will design and deliver production-ready AI solutions, develop tools, APIs, and backend services that enable them, and help shape the future of our AI platform. From evaluation frameworks and deployment pipelines to agentic workflows, you will work across the stack to turn innovation into customer value.

Qualifications

  • Bachelor’s degree in a relevant field; 5+ years of software/ML/AI experience.
  • Proven ownership of production ML/AI systems.
  • Strong Python and backend experience; familiarity with C#, Java, or TypeScript is helpful.

Responsibilities

  • Design, build, and deliver production-ready AI capabilities and services.
  • Develop scalable APIs, microservices, data integrations, and backend systems.
  • Build and improve the infrastructure surrounding AI systems, including monitoring and testing.
  • Prototype and evaluate emerging AI technologies, including LLMs and agentic workflows.
  • Work across cloud infrastructure and data platforms to integrate AI capabilities.

Skills

Python
API design
Microservices
Cloud infrastructure
Kubernetes
Docker
ML/AI systems
LLM / agent workflows
Ownership
Team collaboration

Education

Bachelor’s degree in a relevant field
Advanced degree (MS/PhD)

Tools

Kubernetes
Docker
MLOps

Job description

Q2 is a leading provider of digital banking and lending solutions to banks, credit unions, and fintechs in the U.S. and internationally.

As a Machine Learning Engineer, you will design and deliver production-ready AI solutions, develop tools, APIs, and backend services that enable them, and help shape the future of our AI platform. From evaluation frameworks and deployment pipelines to agentic workflows, you will work across the stack to turn innovation into customer value.

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