Job Description
About Fetch /n Fetch is how modern pet parents give their pets the best care. One pink app for insurance, health and care. /n We’ve raised our Series A from Lightspeed and Airtree, we’re rated 4.9⭐️ on Google, #1 by CHOICE, and we’re growing fast. /n We think AI is going to fundamentally change how we care for pets. /n We have pet health data, an in-house team of vets and vet nurses, and we build our own product and technology. We want to turn that into an intelligence layer that understands each pet deeply – their history, health and what might matter next. /n We’re looking for an exceptional Lead Applied AI Engineer to build it. /n /n The role /n This is a senior, hands-on builder role. /n You’ll lead applied AI at Fetch – setting the direction, choosing the models and approaches, building them yourself, measuring whether they actually work, and shipping them into real products. /n Your core job is simple: make Fetch exceptionally good at understanding pet health. /n That capability will power everything from helping pet parents care for their pets, to supporting vets, interpreting health records and automating parts of insurance. /n We don’t need someone with a particular academic pedigree. We want someone who is obsessed with what modern models can do, moves quickly, experiments constantly and knows how to turn new capabilities into reliable products. /n /n
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Location:
Sydney, hybrid, 3 days in office /n
- /n Employment type: Full time /n
- /n Compensation: Series A salary + meaningful equity /n
- /n Working with: Co-founders, engineering, product, data, vets and vet nurses. We’re flat, fast and care about the best idea. /n /n /n What you’ll build and own /n /n
- /n Fetch’s pet health intelligence layer: models and systems that can understand messy,



longitudinal pet health information and reason over it /n
- /n Model quality end-to-end: datasets, evals, model selection, prompting, retrieval, post-training, fine-tuning, guardrails and monitoring /n
- /n A serious evaluation system: clear benchmarks for what good looks like, where models fail and whether a new model is actually better /n
- /n Domain-specific AI: turning proprietary pet health data and expert veterinary knowledge into capabilities generic models don’t have /n
- /n Multimodal understanding: health records, documents, images and, over time, richer inputs like video /n
- /n Secure production AI: working closely with our vets, compliance and engineering teams to make sure the systems we ship are reliable and clinically appropriate /n
- /n The next generation of Fetch products: you’ll be deeply involved in product direction and help decide what we should build with AI, not simply implement someone else’s roadmap /n
- /n The beginnings of an exceptional AI team: this is a core capability for Fetch and we expect the team around it to grow /n /n You’ll use whatever approach works best. /n Sometimes that will mean a frontier closed-source model. Sometimes an open-source model. Sometimes RAG, tools or better context. Sometimes fine-tuning or post-training. /n We care about getting to the best result, measuring it properly and improving it quickly.



/n /n About you /n You’re an exceptional applied AI builder who wants a lot of ownership. /n You’ve probably spent the last few years building with modern ML and LLMs and have gone much deeper than plugging an API into a product. /n This might look like: /n /n
- /n 3+ years building and shipping ML or AI systems in production /n
- /n Robust experience with contemporary LLMs and applied AI systems /n
- /n Deep understanding of evals – how to construct them, measure model quality and use failures to drive improvement /n
- /n Experience with post-training, fine-tuning, RAG, structured outputs, tool use or similar techniques /n
- /n Strong instincts around training data – what data matters, how to structure it and how to improve its quality /n
- /n Enough engineering ability to take an idea from experiment to production /n
- /n Good judgement about when to use a frontier model, an open-source model, retrieval, fine-tuning or something simpler /n
- /n Strong product thinking – you care what the system enables for the user, not just the benchmark score /n
- /n Comfortable working directly with domain experts to turn human expertise into data, evals and model behaviour /n /n Experience in health, veterinary care or insurance is useful. It isn’t required. /n A PhD isn’t required either. We care much more about what you’ve built, how you think and how quickly you learn. /n /n You’ll probably love this role if: /n /n
- /n You’re all in on AI and believe it can make the world meaningfully better /n
- /n A new model drops and your first instinct is to try it /n
- /n You’re optimistic about where the technology is going and curious about what becomes possible next /n
- /n You’re empirical – you test thin

📌 Lead Applied AI engineer (Sydney)
🏢 Fetch Pet
📍 Sydney