Senior Engineer - ML & AI Systems (AI)

Location: Hybrid in Sydney, Australia, with an additional office location in Melbourne, Australia; office days and collaborative boost days are expected.

Company

hirify.global develops software and AI-powered financial products for small businesses.

What you will do

• Design, build, operate, and own production services, platforms, pipelines, and infrastructure for ML, generative AI, LLM, and agentic systems.
• Build systems supporting JAX, hirify.globalForce, intelligent financial workflows, automated bank reconciliation, and smart document capture.
• Develop orchestration, interfaces, and harnesses that move models into reliable production experiences.
• Improve system scale, latency, cost, reliability, observability, and SLO performance.
• Set engineering standards, mentor engineers, and partner with Applied Scientists, product managers, analysts, and teams across hirify.global.
• Participate in production operations, on-call support, and incident response.

Requirements

• Track record designing, shipping, and operating production-grade backend systems at scale.
• Experience building and operating production systems for LLM or agentic workloads, including orchestration, tool use, evaluation, guardrails, latency, and cost management.
• Strong system design fundamentals and excellent coding in Python or another language suited to web-scale services, such as Go, Java, Kotlin, or TypeScript.
• Experience with APIs, service design, cloud infrastructure, ideally AWS, CI/CD, observability, latency, cost, reliability, and SLOs.
• Experience running services in production, including on-call and incident response.
• Solid SQL skills and experience with large-scale data processing.
• Excellent communication skills for explaining complex technical concepts to business and technical audiences.
• Ability to set engineering standards, coach, and mentor other engineers.

Nice to have

• Experience operationalizing ML or LLM workloads, including inference serving and evaluation pipelines.
• Familiarity with MLflow, PyTorch, TensorFlow, and data orchestration tools.
• Distributed processing experience with Spark or Dask.

Culture & Benefits

• Flexible hybrid working model combining office collaboration with remote-work autonomy.
• Modern office spaces and team-aligned office and collaborative boost days.
• Globally distributed, diverse team of scientists, engineers, product managers, and analysts.
• Collaborative environment focused on reducing toil and delivering reliable intelligent experiences for small businesses.

Hiring process

• Apply even if the experience profile is not a perfect match; hiring considers skills, passion, and the perspective brought to the team.