Senior Computer Vision Engineer - Edge AI & VLMs Lead

Augmodo; Seattle (WA); On-site; USD 170,000 - 200,000; Full time

Benefits offered by this job

Medical

Dental

Vision

401k

Job summary

Augmodo is seeking a tenured Computer Vision Engineer to lead research and production ML for real‑world retail edge deployments. You will bridge research and production, delivering robust CV/VLM solutions and optimizing inference for edge devices.

The role requires a strong publication/academic background and hands‑on industry execution. Expect ~50% R&D and ~50% production work, with expertise in PyTorch, TensorRT, CUDA, Python, and C++.

Qualifications

• 8+ years of substantial industry experience delivering production‑grade computer vision systems with strong academic/research background.

Responsibilities

• Design, implement, and optimize state-of-the-art deep learning, computer vision, and visual-language models for real-world retail edge deployments.
• Bridge research and production code with data-backed analysis to validate algorithm performance against real-world risks.
• Optimize neural network inference for high-throughput, low-latency execution using TensorRT and CUDA optimizations.
• Containerize and deploy ML pipelines using Docker across cloud and edge environments.
• Adopt modern AI‑assisted workflows to maximize engineering throughput and team productivity.

Skills

PyTorch

VLMs

Python

C++

Docker

TensorRT

CUDA optimization

Image registration

Structured analytics

Education

Master's degree in CS/Robotics/EE or related

PhD in CS/Robotics/EE or related

Tools

Docker

TensorRT

CUDA

PyTorch

Job description

Augmodo is seeking a tenured Computer Vision Engineer to lead research and production ML for real‑world retail edge deployments. You will bridge research and production, delivering robust CV/VLM solutions and optimizing inference for edge devices.

The role requires a strong publication/academic background and hands‑on industry execution. Expect ~50% R&D and ~50% production work, with expertise in PyTorch, TensorRT, CUDA, Python, and C++.