Senior Machine Learning Engineer
Q2 Software, Inc.14 days ago
Remote, CanadaSenior
Responsibilities
- Design, build, and deliver production-ready AI capabilities, services, and applications.
- Develop scalable APIs, microservices, data integrations, and backend systems for AI-powered products.
- Build AI-system infrastructure including evaluation frameworks, deployment pipelines, monitoring, observability, and automated testing.
- Prototype and evaluate LLMs, agentic workflows, model integrations, and other emerging AI technologies.
- Work across cloud infrastructure, data platforms, and application layers to integrate AI capabilities.
- Collaborate with product, engineering, data, and platform teams from exploration through production.
Requirements
- Bachelor’s degree in a relevant field and at least five years of related experience, an advanced degree and at least three years of experience, or equivalent related work experience.
- At least five years of professional software, machine learning, or AI engineering experience with meaningful production ownership.
- Strong software engineering fundamentals and experience designing, building, deploying, and maintaining production systems.
- Strong Python skills; experience with C#, Java, or TypeScript 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, and MLOps experience are particularly valuable.
- Experience operating ML or AI systems in production, including evaluation, monitoring, observability, and deployment pipelines.
- Exposure to LLM applications, RAG, agentic workflows, and model or tool integration.
- Ability to work across AI, backend, infrastructure, data, and application code.
- Fluent written and oral English communication skills.
Benefits
- Hybrid work opportunities.
- Flexible time off.
- Health insurance offerings and generous paid parental leave for eligible new parents.
- Career development and mentoring programs.
- Community volunteering, company philanthropy, and Spark Program opportunities.
- Employee peer recognition programs.
- Supportive, inclusive culture prioritizing career growth, collaboration, and physical, mental, and professional well-being.