Senior Machine Learning Engineer

q2ebanking; Austin (TX); Hybrid; USD 120,000 - 190,000; Full time

Benefits offered by this job

Health & Wellness

Hybrid Work Opportunities

Flexible Time Off

Career Development & Mentoring

Health Insurance & Parental Leave

Volunteer Programs

Peer Recognition Program

Job summary

Q2 is seeking a Machine Learning Engineer to design and deliver production-ready AI solutions for the financial services sector. You will build APIs, microservices, and backend services enabling AI-powered workflows, while collaborating across product, engineering, and data teams to ship high‑quality, enterprise-grade software.

The role emphasizes owning end-to-end AI systems, evaluating new AI technologies, and partnering to turn innovative ideas into customer value.

Qualifications

• Typically requires a Bachelor's degree in (relevant degree) and a minimum of 5 years of related experience; or an advanced degree with 3+ years of experience; or equivalent related work experience.
• 5+ years of professional software/ML/AI engineering experience, with meaningful production ownership.
• Strong software engineering fundamentals and a track record of designing, building, deploying and maintaining production systems.
• Strong Python, while experience with other backend/application languages such as C#, Java, TypeScript, etc. is valuable.

Responsibilities

• Design, build, and deliver production-ready AI capabilities, services, and applications that solve real customer and business problems.
• Develop scalable APIs, microservices, data integrations, and backend systems that enable AI-powered products and workflows.
• Build and improve the infrastructure surrounding AI systems, including evaluation frameworks, deployment pipelines, monitoring, observability, and automated testing.
• Prototype and evaluate emerging AI technologies, including LLMs and agentic workflows, and turn successful ideas into reliable, enterprise-grade solutions.
• Work across cloud infrastructure, data platforms, and application layers to integrate AI capabilities into the broader Q2 technology ecosystem.
• Collaborate closely with product, engineering, data, and platform teams to define solutions, make technical tradeoffs, and take ideas from early exploration through production

Skills

Python proficiency

Cloud experience

ML/AI engineering

Distributed systems

English communication

Education

Bachelor's degree in relevant field

Advanced degree

Tools

Kubernetes

Docker

MLOps

LLMs

Job description

As passionate about our people as we are about our mission.

Why Join Q2?

Q2 is a leading provider of digital banking and lending solutions to banks, credit unions, alternative finance companies, and fintechs in the U.S. and internationally. Our mission is simple: build strong and diverse communities through innovative financial technology-and we do that by empowering our people to help create success for our customers.

What Makes Q2 Special?

Being as passionate about our people as we are about our mission. We celebrate our employees in many ways through our year-round Q2 ChangeMakers awards program and global moments of recognition and connection. We invest in the growth and development of our team members through ongoing learning opportunities, internal mobility, and meaningful leadership relationships. We also know that nothing builds trust and collaboration like having fun and giving back together. From company-wide volunteer days to events like our Q2 Homecoming Week-featuring learning, community service, and culture-building experiences-we create opportunities to connect, grow, and make an impact.

The Job At-A-Glance:

Join a fast-growing AI engineering team building the next generation of intelligent products for the financial services industry. As a Machine Learning Engineer, you'll design and deliver production-ready AI solutions, develop the tools, APIs, and backend services that enable them, and help shape the future of our AI platform. From evaluation frameworks, deployment pipelines, and microservice-based AI capabilities to next-generation agentic workflows, you'll have the opportunity to work across the stack, prototype new ideas, and turn innovation into real customer value. We're looking for engineers who are passionate about technology, committed to building high-quality, enterprise-grade software, and who thrive in collaborative environments. The ideal candidate stays current with the rapidly evolving AI landscape, enjoys solving meaningful problems, and is excited to help build innovative solutions alongside a team that values creativity, ownership, continuous learning, and shipping great products.

A Typical Day:

• Design, build, and deliver production-ready AI capabilities, services, and applications that solve real customer and business problems.
• Develop scalable APIs, microservices, data integrations, and backend systems that enable AI-powered products and workflows.
• Build and improve the infrastructure surrounding AI systems, including evaluation frameworks, deployment pipelines, monitoring, observability, and automated testing.
• Prototype and evaluate emerging AI technologies, including LLMs and agentic workflows, and turn successful ideas into reliable, enterprise-grade solutions.
• Work across cloud infrastructure, data platforms, and application layers to integrate AI capabilities into the broader Q2 technology ecosystem.
• Collaborate closely with product, engineering, data, and platform teams to define solutions, make technical tradeoffs, and take ideas from early exploration through production

Bring Your Passion, Do What You Love. Here's What We're Looking For:

• Typically requires a Bachelor's degree in (relevant degree) and a minimum of 5 years of related experience; or an advanced degree with 3+ years of experience; or equivalent related work experience.
• 5+ years of professional software/ML/AI engineering experience, with meaningful production ownership.
• Strong software engineering fundamentals and a track record of designing, building, deploying and maintaining production systems.
• Strong Python, while experience with other backend/application languages such as C#, Java, TypeScript, etc. is valuable.
• Experience building APIs, backend services, microservices, data integrations or distributed systems.
• Hands‑on experience with cloud infrastructure, containers and production deployment; Kubernetes/Docker/MLOps experience is particularly valuable.
• Experience building or operating ML/AI systems in production, including evaluation, monitoring, observability and deployment pipelines.
• Exposure to LLM applications, RAG, agentic workflows, model/tool integration or similar modern AI patterns.
• Ability and willingness to work across traditional boundaries-AI, backend, infrastructure, data and occasionally UI/application code.
• Strong ownership, curiosity and comfort operating in an environment where patterns and solutions are still being established.

This position requires fluent written and oral communication in English.

Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

• Health & Wellness
• Hybrid Work Opportunities
• Flexible Time Off
• Career Development & Mentoring Programs
• Health & Wellness Benefits, including competitive health insurance offerings and generous paid parental leave for eligible new parents
• Community Volunteering & Company Philanthropy Programs
• Employee Peer Recognition P