Staff ML Platform Engineer (MLOps)

Location: Remote in the United States or Canada. Toronto-based candidates may optionally work from the Toronto office; approximately 2–3 trips per year are expected.

Salary: USD $172,000–$215,000 in the United States / CAD $172,000–$220,000 in Canada

Company

hirify.global is a SaaS and AI company building workforce development technology that helps people find better jobs and supports organizations serving job seekers.

What you will do

• Assess existing data pipelines, ML workflows, and architecture, then create and execute a prioritized platform plan.
• Build reproducible compute, training, serving, deployment, and environment-management foundations.
• Develop LLM infrastructure with model routing, prompt and response evaluation, and cost and latency optimization.
• Establish safe model experimentation through A/B tests, shadow deployments, canaries, holdouts, and predefined success criteria.
• Implement monitoring, alerting, regression detection, lineage, and traceability for production recommendations.
• Operate production ML systems, debug incidents, and maintain consistent feature computation between training and inference.

Requirements

• Staff-level hands-on experience in MLOps, ML platforms, ML infrastructure, data platforms, or equivalent platform ownership.
• Experience building model CI/CD, experiment tracking, registries, deployment workflows, and monitoring end to end.
• Production experience with LLM systems, including serving, evaluation, model routing, and cost and latency tradeoffs.
• Experience operating both batch and real-time models, including containers, reproducible environments, and compute provisioning.
• Strong observability, traceability, data engineering, systems design, and production incident-debugging experience.
• Must be located in the United States or Canada.

Nice to have

• Feature store experience and interest in growing into model development.
• Experience evaluating AI/ML observability or LLM evaluation vendors.
• Mission-driven, workforce, or government-adjacent data experience.
• Experience mentoring a small data and engineering team.

Culture & Benefits

• Remote-first work with an optional Toronto office arrangement.
• High-velocity, high-trust environment focused on meaningful workforce impact.
• Approximately 2–3 company trips per year, including an annual August off-site.
• Values include curiosity, outcome ownership, continuous improvement, speed, and collaboration.
• Equal opportunity workplace with reasonable accommodations available during hiring and employment.

Hiring process

• Online application and initial Talent Acquisition screen.
• Hiring manager interview followed by a performance challenge.
• Final one-to-one interviews and decision; the process generally takes about six weeks.