Machine Learning Engineer

🏦 Senior Machine Learning Engineer Generative AI & MLOps (Fintech)

📍 Sydney (Hybrid) | 💼 Full time | 💰 $160k to $200k + Equity

🚀 Rapidly Scaling Fintech | 🎯 Immediate Start

The Opportunity

I’m working with a fast-growing, venture backed fintech scale up that’s redefining how regulated industries use AI. They’re building real time infrastructure for onboarding, fraud detection, and compliance, and they’re now looking for a Senior Machine Learning Engineer with deep AWS expertise to help scale their generative AI capabilities in production.

This is your chance to work hands on with sensitive financial data, optimise low latency LLM systems, and design secure, auditable ML pipelines in a fully AWS based environment.

• Why You Should Consider This Role
• Build and deploy LLM based compliance and risk systems using AWS native tooling
• Lead end to end MLOps pipeline architecture on a high scale AWS infrastructure
• Work with secure, regulated data and apply best practices for auditability and governance
• Own performance, cost, and security of ML models in production on AWS
• Collaborate in a high trust, low ego team solving enterprise grade AI challenges

About the Company

This is a fintech company committed to transparency, trust, and explainability in AI. Their products are used by digital banks, asset managers, and credit providers who require precision and compliance, not just predictions. With strong investor backing and proven traction, they’re now scaling their machine learning capability and AWS infrastructure globally.

What You’ll Be Doing

• Fine tune and serve LLMs for KYC, fraud detection, and document classification via AWS services
• Build retrieval augmented generation (RAG) pipelines using tools like Amazon OpenSearch, Bedrock, or SageMaker
• Design CI/CD workflows for ML model training, testing, deployment, and monitoring entirely on AWS
• Implement data pipelines, feature stores, and model versioning using AWS Glue, S3, Lambda, and Step Functions
• Optimise model latency and performance for real time inference on SageMaker endpoints
• Ensure security, compliance, and auditability across the ML lifecycle in a regulated AWS hosted environment

What They’re Looking For

• 5+ years in applied ML, ideally in fintech or another high integrity industry
• Strong Python engineering skills and deep familiarity with Hugging Face and transformer models
• Solid hands on experience with AWS services such as SageMaker, Lambda, Step Functions, S3, Glue, and CloudWatch
• Proven experience building MLOps workflows using AWS native tools
• Familiarity with financial risk models, regtech, or document automation
• Bonus Knowledge of Bedrock, model explainability on SageMaker, or compliance focused ML design

What’s on Offer

• 💰 $160k to $200k base + equity
• 🔐 Work in secure, high impact AI systems with direct access to financial data
• 🌍 Hybrid Sydney office with flexible remote options
• 📚 $3k learning and development allowance
• 🧠 Real world ML problems in high throughput, low latency AWS environments
• 🚀 Career pathway into Lead ML Engineer or System Architect roles

Interested?

If you're ready to shape the future of real time generative AI using AWS, send your CV to [email protected] or click Apply Now to chat further.

Let’s build something transformative together.