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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Machine Learning Engineer - **Company:** Q2 Software, Inc. - **Location:** Austin, TX, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Application Layers, Automation of Tests, C Sharp (Programming Language), Cloud Computing, Data Integration, Distributed Systems, Python (Programming Language), Machine Learning, Software Deployment, TypeScript, Delivery Pipeline, Large Language Models, Backend, AI Platforms, Kubernetes, Data Management, Machine Learning Operations, Api Design, Restful APIs, Docker, Microservices - **Published:** September 5, 2026 - **Apply:** https://q2ebanking.wd5.myworkdayjobs.com/Q2/job/Austin-TX/Senior-Machine-Learning-Engineer_REQ-12664 ## About the Role * 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. ## Description 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 ## Related Videos - [API Design - Getting Started](https://www.wearedevelopers.com/videos/33-api-design-getting-started) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Agentic AI Systems for Critical Workloads](https://www.wearedevelopers.com/videos/1592-agentic-ai-systems-for-critical-workloads) - [Rest API Antipatterns](https://www.wearedevelopers.com/videos/100208-rest-api-antipatterns) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Why Upskilling And Reskilling is Important For Developers](https://www.wearedevelopers.com/magazine/428-why-upskilling-and-reskilling-is-important-for-developers) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)