Founding Machine Learning 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.