Production AI Engineer — Multimodal Systems & Privacy

Noösphere; Seattle (WA); On-site; USD 150,000 - 230,000; Full time

Job summary

Noösphere is seeking an experienced research engineer to drive productionization of multimodal models, data pipelines, and privacy-compliant training workflows. You will own training infrastructure, evaluation suites, and inference latency across edge and cloud, while ensuring governance and data protection across real-world deployments.

You’ll collaborate with research on models, data, and telemetry, balancing pragmatic engineering with ambitious, high-ownership work in a small, fast-moving

Qualifications

• 5+ years building and shipping ML systems in production.
• 2+ years deploying models to real users.
• Strong software fundamentals in Python and systems code.

Responsibilities

• Take models to production: export, quantization, distillation, and real-time inference across edge and cloud.

Skills

ML systems in production

Distributed training

Privacy-preserving pipelines

Eval harnesses & benchmarks

Real-time inference

Data pipelines for model training

Edge/Cloud deployment

Privacy governance

Tools

PyTorch

ONNX

TensorRT

Triton

vLLM

AWS

GCP

Kubernetes

Python

C++

Rust

Go

Job description

Noösphere is seeking an experienced research engineer to drive productionization of multimodal models, data pipelines, and privacy-compliant training workflows. You will own training infrastructure, evaluation suites, and inference latency across edge and cloud, while ensuring governance and data protection across real-world deployments.

You’ll collaborate with research on models, data, and telemetry, balancing pragmatic engineering with ambitious, high-ownership work in a small, fast-moving