Description

You will lead the architectural evolution of our safety systems, building a unified Perception Platform Layer that translates raw sensor data into real-time, high-stakes decisions. This role focuses on platform architecture unification, performance reliability engineering, rigorous evaluation, and technical leadership to ensure reliable model performance across cloud and edge environments.

Requirements

• Experience leading architectural evolution of ML systems
• Expertise in real-time ML system design and deployment
• Proficiency in hybrid edge-cloud model orchestration
• Strong background in performance engineering and observability
• Ability to develop evaluation frameworks for rare safety events

Responsibilities

• Architect a Unified Perception Layer from fragmented models to modular platform
• Design and implement real-time ML systems for sensor ingestion, tracking, risk reasoning, and actuation
• Orchestrate model integration across edge and cloud environments with versioning and fallback mechanisms
• Own end-to-end latency and reliability for safety-critical pipelines
• Build sophisticated monitoring for deployed models to detect drift and latency regressions