Senior AI/ML Engineer Fintech/Lending Sydney – Hybrid $190k Super Our client, in the boutique non-bank lending space, are looking for a highly skilled Senior AI/ML Data Engineer, ideally from a loan market/credit risk environment to own the end-to-end design and delivery of AI systems - from data and model development through to production serving, monitoring, and continuous improvement. You’ll partner with engineering, product, risk, and compliance to deliver measurable business impact in lending, customer experience, fraud, collections, and operations automation. Responsibilities · Design clean, scalable architectures for AI/ML services using SOLID principles and proven design patterns. · Build reliable microservices and event-driven components for inference, retrieval, and agent orchestration. · Lead technology selection, trade-off analysis, and roadmap creation for GenAI · Develop and tune LLMs using LoRA/QLoRA and, where needed, full fine-tuning. · Implement advanced prompt engineering, few-shot techniques, and evaluation frameworks. · Architect robust RAG pipelines with optimal chunking, embeddings, vector stores, and knowledge graphs. · Design multi-agent workflows (LangGraph, AutoGen, CrewAI, Pydantic AI) with strong state management and guardrails. · Build and productionise ML/DL models with PyTorch/TensorFlow, including ensembles and reinforcement learning for optimisation/agent policies. Skills and Experience · Expert Python, including async/await, memory/performance profiling, and production-grade code quality. · Strong grasp of clean architecture, design patterns, and testing strategies. · Deep experience with ML algorithms, deep learning, and reinforcement learning for decisioning/optimisation. · Proven track record with LLM fine-tuning, prompt engineering, and advanced RAG system design. · Familiarity with multimodal models for document understanding and customer interaction. · Hands-on experience with Docker, Kubernetes, CI/CD, infrastructure as code. · Proficiency across AWS/GCP/Azure; strong understanding of managed AI services and when to use them. · Experience with high-performance serving, observability, A/B testing, and cost optimisation. · Expertise with SQL, vector databases, and distributed systems patterns. · Strong API design and real-time systems experience; ETL/ELT and stream processing know-how. · Practical knowledge of AI safety, red-teaming, prompt injection prevention, PII handling, and model/feature governance. · Awareness of financial services compliance requirements and model risk management. If this opportunity speaks to you and your skills and experience directly align, please submit application with relevant CV attached.
