АвстралияSenior Software Engineer - ML & AI (AI Products)
5 дн. назад
АвстралияSeniorHybrid
pythonml engineeringllminfrastructure
Design, build and operate production systems behind AI features and large language model-powered experiences.
Обязанности
- You will design, build and own the production systems behind ’s AI features: the services, pipelines and infrastructure that power LLM-driven and agentic experiences for millions of small businesses every day. This is a software engineering role. You’ll build and operate systems rather than train or tune models, and your architecture decisions will directly shape scale, cost, reliability and how fast our teams ship.
- You don’t need a machine learning background. We’re looking for strong production engineers, ideally with experience building LLM or agentic systems, and ML depth can be learned on the team.
- Beyond architecture, you’ll lift engineering capability across AI Products by setting standards, mentoring engineers and partnering across to make data usable and systems dependable.
Будет плюсом
- Experience operationalizing ML or LLM workloads (inference serving, evaluation pipelines)
- Familiarity with MLflow, PyTorch or TensorFlow, and data orchestration tools
- Distributed processing experience (Spark, Dask)
- Apply even if your experience isn't a perfect match! At , we hire based on your skills, passion, and the unique perspective you can bring to enhance our culture and team.
Другое
- You’ll join AI Products, a diverse, globally distributed team of scientists, engineers, product managers and analysts within our broader Data & AI business.
- Engineers here partner closely with Applied Scientists early on to build the interfaces and harnesses that take models into production. They then own the engineering and infrastructure of every ML and AI system shipped into production, from reliability and cost to scale. Together, this collaborative team reduces toil and delivers reliable, intelligent experiences for small businesses.
- Production ML and AI engineering: Building and operating the platforms, services and practices that support traditional ML models, generative AI and agentic systems in production.
- JAX (Just Ask ): Powering 's conversational GenAI assistant and evolving the underlying capabilities to support increasingly sophisticated, context-aware and agentic experiences.
- Intelligent financial workflows: Developing capabilities such as Automated Bank Reconciliation and smart document capture, using ML and AI to match transactions, extract information from bills and receipts, and automate complex tasks.
- XeroForce: Building the platform for AI-powered workflows, enabling agents to plan and execute complex tasks across ’s products and supporting reliable, reusable agentic experiences at scale.
- End-to-end AI product experiences: Integrating AI into customer-facing experiences and product workflows, alongside the backend services, orchestration and infrastructure that make them work.
- offers a flexible hybrid working model designed to blend the collaboration of office life with the autonomy of remote work. You will have access to our modern office spaces, with expectations around office days and collaborative 'boost days' aligned to help your team connect and ship great code effectively.
- A track record of designing, shipping and operating production-grade backend systems at scale
- Experience building and operating production systems for LLM or agentic workloads (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 (Go, Java, Kotlin, TypeScript)
- Experience with APIs and service design, cloud infrastructure (ideally AWS), CI/CD and observability, with a focus on latency, cost, reliability and SLOs
- Experience running services in production, including on-call and incident response
- Solid SQL and experience with large-scale data processing
- Excellent communication, with the ability to explain complex technical concepts to business and technical audiences
- A coaching mindset and the ability to set engineering standards and mentor other engineers