Machine Learning Performance Engineer

Company Letly is an AI-Native vertical fintech platform focussed on the rental housing market. We are automating rental workflows end-to-end and building a fintech platform underneath to manage the trillions of dollars spent on rent globally. We recently closed a pre-seed round and are hiring one talented AI/ML engineer with a strong software engineering background and a passion for deploying AI/ML models into real-world, production-grade applications. Apply if: You have strong foundational software engineering knowledge, including data structures, algorithms, system design, and OOP. You have advanced knowledge of LLM architectures and ML/DL frameworks (e.g. TensorFlow, PyTorch, LangChain, Keras, scikit-learn). You're ready to design, deploy and maintain production-grade Machine Learning systems. You're willing to champion best practices in code quality, testing, observability and MLOps. You have experience with MLOps tools and practices (CI/CD, Docker, Kubernetes) and cloud platforms (GCP, AWS, or Azure). You're a smart, intense, and focussed individual willing to build things efficiently in a close team. You want to tackle large technical hurdles, and build first-of-its-kind software using AI. You will: Write high-quality, maintainable, well-documented, and tested code, adhering to software engineering best practices. Design, implement, and deploy production-grade AI/ML models to address various platform needs (including NLP and OCR). Optimise AI models and associated systems for performance, scalability, and cost-effectiveness in a production environment. Implement and manage the infrastructure for MLOps, including fine-tuning, deployment, monitoring and versioning. Develop robust data pipelines for ingestion, cleaning, model training, and continuous deployment. Build retrieval-aware repositories for model training, evaluation, and real-time context-rich inference. Collaborate closely with the software engineers to integrate AI models seamlessly into the platform architecture using APIs. Be a key part of a high-performance, engineering and product-led company with a high degree of autonomy and impact. Compensation: Competitive salary and meaningful equity in the company. Annual performance-based compensation (cash and equity). Opportunity for true meritocratic progression in role and compensation. Example deliverables (first 90 days): Stand-up the rule-evaluation core of the compliance microservice: JSONLogic/CEL engine to load rule set from Mongo and return pass/fail result. Wire a Pub/Sub sink to integrate with the rest of the system, emitting ComplianceDecision events, and land these in BigQuery for analytics. Light-up observability – deploy OpenTelemetry traces + Grafana dashboards, and config alerts for latency, failure %, override rate.