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About the role
Responsibilities
Own system behavior and data pipelines.
Design ingestion → reasoning → decision systems.
Improve the decision layer for consistency and reliability.
Close the loop from deployments → system learning.
Ensure system reliability across device, cloud, and partial connectivity.
Partner with RF / hardware / field teams to deliver for elite users globally (~10–15% travel).
Requirements
5–10 years building and operating production systems.
Strong system design across APIs, pipelines, and data storage.
Deployed ML / LLM systems in production and improved them via feedback loops.
Strong Python, plus Go/TypeScript (or similar).
Comfortable working across device and cloud environments.
Able to debug production systems quickly and decisively.
Communicates clearly and operates independently.
U.S. Person status required.
Nice-to-Haves
Built RF / BLE classification systems and models from zero.
Handled streaming systems (Kafka, pub/sub).
Created LLM pipelines (prompting, retrieval, evaluation).
Designed for adversarial or security environments.
Built systems that run on-device as well as in the cloud.
Thrived in early-stage startup environment.
Compensation
Base salary up to $240,000, depending on qualifications, experience, and impact.
Total compensation includes equity, premium insurance, 401(k), flexible PTO, and other individual benefits.
Skills
PythonGoTypeScriptMachine LearningLLMsAPIsData PipelinesKubernetesKafkaStreaming Systems
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Salary not listed
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