Machine Learning Engineer

What makes this role special?
First dedicated AI systems hire.
You’re the difference between a system that exists and one that works.
Ensure reliability of the entire AI system—from data ingestion to operator decision.
Turn noisy cyber-physical observations into trusted operational decisions.
Define how the system reasons under uncertainty.
Your work is used in high-stakes environments where outputs must be trusted.
Become the technical lead for Sweep’s AI decision system before Series A.

What we’re looking for...
5–10 years owning production systems end-to-end.
Strong system design across APIs, pipelines, and data storage.
Built production AI systems trusted in real-world operations.
Strong Python, plus Go/TypeScript (or similar).
Comfortable building systems spanning edge devices, cloud, and intermittent connectivity.
Able to debug production systems quickly and decisively.
Communicates clearly and operates independently.
U.S. Person status required (may involve export-controlled data).

Bonus if you’ve...
Handled streaming systems (Kafka, pub/sub).
Created production LLM or inference pipelines (prompting, retrieval, evaluation).
Designed for adversarial or security environments.
Built systems that run on-device as well as in the cloud.
Thrived in an early-stage startup environment..

What you’ll do...
Shape how the production AI system behaves in the real world.
Design ingestion → reasoning → decision systems.
Drive inference reliability, predictable logic, and transparent reasoning.
Close the loop from deployments → system learning.
Make the system trusted under real-world conditions.
Partner with RF / hardware / field teams to deliver for elite users globally (~10–15% travel).