The alarm system for e-commerce operations.
Our mission is to detect and disrupt the risks - from delivery fraud to "Item Not Received" (INR) claims - that create friction between merchants, carriers, and 3PLs. We sit at the intersection of e-commerce, logistics, and fraud, turning massive, complex data streams into the clear-cut intelligence our clients need to operate safely.
We're a growing pod of a Data Scientist (the brain) and a Data Engineer (the infrastructure). We are now looking for the critical third member: the Machine Learning Engineer who will build and deploy our intelligence into production.
Ship the intelligence to production.
As our Founding Machine Learning Engineer, you will be the builder who productionizes our intelligence. This isn't a role for R&D - this is a role for building, shipping, and scaling our models.
You will be the hands-on partner to our Data Scientist. They will come to you with a model prototype and a "why" - you will be the one who knows "how" to build it into a low-latency, high-availability, production-grade service.
Your challenge is to build the MLOps foundation and the APIs that are our product. You will own the full lifecycle of our models, from deployment to monitoring, ensuring our alarm system is always-on, fast, and reliable.
Own it end to end.
Partner with our Data Scientist to take model prototypes and build, deploy, and scale them in a production environment.
Design and build the robust, low-latency APIs that serve our model's predictions to our core platform.
Own our MLOps tooling, building the systems for CI/CD, training, and monitoring.
Obsess over model speed, reliability, and accuracy. Ensure our models can handle real-time, high-volume traffic.
You are a software engineer first, who specializes in ML. You will write clean, testable, and maintainable code.
Define the data-serving requirements for your models, ensuring the infrastructure and intelligence are perfectly in sync.
Sound like this.
4+ years of hands-on experience as a Machine Learning Engineer or Software Engineer with a focus on ML.
Fluent in Python with deep experience building and deploying ML models (e.g., scikit-learn, TensorFlow, PyTorch).
A production-first builder with experience building and managing real-time APIs (e.g., FastAPI, Flask) and containerization (e.g., Docker, Kubernetes).
Hands-on experience with MLOps tooling and cloud platforms, especially GCP.
Obsessed with reliability and automation. You believe that if a model isn't monitored and automated, it isn't done.
A builder who shows, not tells. You prove how good you are by shipping elegant, working solutions.
Thrives on autonomy and ownership. You want guidance, not guardrails.
A listener and a collaborator. You know the best ideas come from group conversations and you're eager to build a common vision with a small, brilliant team.
Small team. Hard problems.
We are a small team of passionate, curious people dedicated to solving hard problems. Our culture is our foundation.
We give you the freedom, trust, and tools to build end-to-end solutions.
We're critical thinkers who obsess over the details. The best solution is rarely the first one.
Everyone talks to everyone. Your voice and your ideas are critical from day one.
We are building the best infrastructure for our team to create their best work.
Ready to build?
If you are a curious, resilient builder who wants to own a core part of a new product, we would love to talk.
Apply now →
