Staff Machine Learning Engineer

Scouut Sydney, New South Wales, Australia Get AI-powered advice on this job and more exclusive features. Scouut provided pay range This range is provided by Scouut. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more. Base pay range A$210,000.00/yr - A$250,000.00/yr Want to Build the AI Engine Driving the Future of Sustainable Packaging? As the Founding AI/ML Engineer , you’ll take on that very responsibility and partner with an A-team of 6 world-class talents (including you) to solve incredibly complex AI-powered challenges at scale. As you might have guessed, you’ll take full ownership of the AI/ML platform - architecting it for massive scale from the ground up and building it through to production. You’ll join an early-stage startup with both US & European funding, helping to build the software platform that turns complete document and data chaos into blissful clarity. That data? Packaging data. Stored everywhere - PDFs, spreadsheets, supplier portals, disconnected PCs, inboxes belonging to people who left years ago - literally everywhere. And with governments demanding clean, faultless reporting from global companies handling incomparable volumes of messy, unstructured data - they need what you’re building. Best of all? You’ll help enable better, greener, more sustainable packaging decisions for companies globally. It’s a win for you, your customers, and the planet. Sound interesting? Good - let’s read on. Why This Role Will Change Your Career You’ll architect the core. As the founding AI/ML engineer, you’ll be the domain specialist with complete autonomy across that part of the platform. You’ll build something that matters. Every workflow you automate helps customers make faster, greener packaging decisions - and hit sustainability targets they couldn’t reach before. You’ll work with elite peers. A small, high-performing team with deep software, data, and operational expertise, backed by respected investors across the US and EU. You’ll be joining at the start of the J-curve. Governments are mandating this work; the alternative is thousands of hours of manual processing. You’re joining a shovel company at the beginning of the gold rush. You’ll be rewarded properly. $210k-$250k+Super plus an early-stage ESOP package that reflects your ownership and impact. What You’ll Do You’ll own the ML and AI layers that helps transform obscene amounts of highly complex, unstructured packaging data into structured intelligence: Build AI-powered extraction, matching, and inference pipelines for data that comes in all sorts of shapes and sizes, from a huge amount of different locations - all under strict guardrails that prevent hallucinations. Define data/feature representations and evaluation methods that keep outputs verifiable, audit-ready, and reportable. Design and operate training and inference workflows with reliability, observability, and specific latency/throughput targets. Partner with the Backend specialist to productionise models behind internal/external APIs and supplier integrations. Build reliability into AI systems: deterministic constraints, fallbacks, confidence thresholds, monitoring, and SLAs. Drive cost/performance optimisation across AWS for data processing and inference. Collaborate across product/engineering to decide where ML adds leverage vs. where deterministic rules are better, then implement. Document, mentor, and set standards for the engineers who’ll eventually follow your lead. You’re a Staff Level Engineer who’s built and shipped production ML systems end-to-end in startup or scaleup environments - from prototype to serving and monitoring. You’re fluent in Python and SQL , strong with PyTorch/TensorFlow , and confident building data pipelines, training workflows, and evaluation frameworks. You’ve designed and deployed model-backed APIs and services that are reliable, observable, and meet strict SLAs — including cost and performance tuning on AWS. You know how to build safe, deterministic AI systems - using rules + ML, guardrails to avoid hallucinations, RAG, constrained decoding, and human-in-the-loop workflows where needed. You’ve delivered real value from unstructured data (OCR, NLP, document intelligence, computer vision, entity matching and/or similar) and know how to turn models into scalable, fault-tolerant production systems. About the Mission Packaging data today is scattered - images, PDFs, supplier portals, spreadsheets, even paper tucked away in drawers. Our client is building the AI-powered infrastructure that unifies it all into a single source of truth - automatically. It saves customers hundreds of hours in reporting, unlocks grants and rebates, and, most importantly, helps them make better sustainability decisions. They’re very well funded, building with a Silicon Valley mindset, and want you to take ownership of a core part of the product. What This Is (and Isn’t) ✅ A founding-level role with full ownership of AI/ML design and delivery. ✅ Flexible hybrid setup (Sydney-based; typically 1-2 office days per week). ❌ A pure research position - you will apply ML pragmatically and ship it to production with strong guardrails. ❌ An LLM only AI role. You’ll need to come from a “traditional ML” background and have exposure to ML models in the pre-LLM days, as well as modern LLM tooling. ❌ Not a “boring packaging-focused role” - this is pushing modern AI and software to its limits at insane scale. Ready to turn chaos into clarity and positively impact the planet along the way? If you want to use your engineering talent to accelerate the world’s shift to sustainable packaging - and own the AI/ML systems making it possible - we’d love to speak. Hit apply or reach out to for a chat Seniority level Director Employment type Full-time Job function Information Technology Industries Software Development Referrals increase your chances of interviewing at Scouut by 2x Sydney, New South Wales, Australia 6 days ago #J-18808-Ljbffr