Edge Dialog AI Engineer (On-Device & Safety-Critical)

Socket.dev; Palo Alto (CA); Hybrid; USD 180,000 - 260,000; Full time

Job summary

BrightAI seeks a Senior AI Engineer to own edge dialog systems for its safety-critical wearable. You will advance on-device NLUs, multi-turn pipelines, and deterministic safety layers, ensuring low latency and energy use while maintaining high accuracy.

You will work across NLP, embedded software, and ML tooling to deploy models on constrained hardware, with a focus on reliability and scalable deployment across customers.

Qualifications

• 5+ years in ML/AI with NLP/LLMs or conversational AI focus.
• Applied background in NLU, dialog systems, or on-device ML.
• Strong Python, testing (pytest), Git, and CI discipline.

Responsibilities

• Own end-to-end on-device dialog pipeline: intent routing and classification.
• Maintain deterministic safety layer around LM-confirmation and gating.
• Run SLM inference on-device within memory and latency budgets; optimize.
• Extend zero-shot config model for rapid customer onboarding.
• Coordinate device deployment with edge team; maintain STT pipeline.
• Define on-device benchmarks for latency and accuracy; drive decisions.
• Build golden datasets and non-regression suites as release gates.

Skills

NLP/LLMs/conversational AI

LLM prompting & RAG

Python programming

On-device inference

Edge systems engineering

Deterministic safety & gating

Experimentation & benchmarking

Problem solving & communication

Education

B.S./M.S. in AI/ML/EE/CS

Tools

Python

ONNX/onnxruntime

Docker

Linux

Job description

BrightAI seeks a Senior AI Engineer to own edge dialog systems for its safety-critical wearable. You will advance on-device NLUs, multi-turn pipelines, and deterministic safety layers, ensuring low latency and energy use while maintaining high accuracy.

You will work across NLP, embedded software, and ML tooling to deploy models on constrained hardware, with a focus on reliability and scalable deployment across customers.