Staff Machine Learning Engineer

The role / impact In this role, you will play a critical part in designing, building, and deploying backend generative AI solutions that power automated, intelligent workflows. You will take ambiguous, complex R&D problems and convert them into production-ready software, ensuring our models are robust, scalable, and secure. Your engineering expertise will directly shape our machine learning architecture, ensuring the team maintains absolute ownership of the production-grade code that moves into deployment. By championing technical excellence and acting as a role model, you will drive clarity across teams and elevate our overall technical capabilities. The team / how they connect You will join the AI North America team, a highly collaborative and innovative group of around 40 people working remotely across Canada and the US in the PST timezone. The team consists of applied scientists and engineers who work together closely on cutting-edge Agentic AI implementations within an agile framework. Together, you will focus on building AI-native user experiences and driving technical clarity in a supportive environment. The team is currently working on Developing JAX 3.0, transitioning our chatbot into a next-generation, AI-native platform for work Building the infrastructure and workflows required for agentic performance and evaluation Evaluating, rewriting, and adapting models into production-grade backend solutions Optimising our core technical stack which includes Python, AWS, Kubernetes, PydanticAI, and Temporal Where and how you can work This is a fully remote position within Canada, with a preference for candidates based in Vancouver, though Toronto is also an acceptable location if you are willing to work in Pacific Standard Time (PST). Our team connects primarily through virtual meetings and Slack. While you will enjoy full remote flexibility, you will also have access to our modern office spaces for intentional collaboration and scheduled team boost days. Here are some of the things we are looking for A strong background in building highly scalable backend engineering solutions in cloud environments The ability to independently navigate ambiguity and translate complex challenges into clear, working technical solutions Curious and fluent with AI tools, knowing how to leverage them to accelerate research and development without compromising on code quality A deep sense of ownership and understanding of code, with a commitment to maintaining 100% accountability for everything moved into production Excellent communication skills to align effectively with product managers, project managers, and R&D leaders across the business Familiarity with Python, Kubernetes, GenAI, machine learning concepts, or frontend interfaces would be a welcome addition to the team Apply even if your experience isn't a perfect match! At Xero, we hire based on your skills, passion, and the unique perspective you can bring to enhance our culture and team. At Xero, we value the impact and skills you bring to the team. We believe in a Total Package philosophy - ensuring your value is recognized through a holistic lens that includes base salary, performance incentives, and world-class benefits. The expected base salary range for this role is $195,000 - $235,000 CAD. Individual pay is determined by various factors, including geography, level of experience, and the specific skills you bring to the role. In addition to base pay, Xero’s roles are eligible for the following forms of variable compensation: Variable Pay: Permanent employees are eligible to participate in our annual bonus and equity (RSU) programs. You may also be eligible for performance-based cash or equity (RSUs) incentives depending on your role level, and company performance. Comprehensive Benefits: World-class health, wellness, and retirement programs. Xero Perks including Wellbeing days, generous leave, and dedicated professional development budgets. This is a posting for an existing vacancy. Xero uses AI to help screen applications based on job-related qualifications. These tools assist our recruiters but do not make automated hiring decisions. A human recruiter reviews all candidates before any hiring action is taken.