Computer Vision Engineer

AUGMODO INC.
United States
8 days ago
Apply on jobs.ashbyhq.com
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
8 years minimum
Compensation
$170,000.0 - $200,000.0
Working hours
Regular working hours

Tech stack

Artificial Neural Networks Computer Vision C++ (Programming Language) Nvidia CUDA Computer Engineering Image Registration Python (Programming Language) Language Modeling Pytorch Deep Learning Containerization Production Code
+3 more
Machine Learning Operations TensorRT Docker

Job description

Leads advanced computer vision R&D and production engineering for real-time retail edge deployments. Designs and optimizes deep learning, computer vision, and vision-language models; validates algorithms through evidence-based analysis; and deploys high-throughput, low-latency ML pipelines. Responsibilities include TensorRT and CUDA optimization, Docker-based cloud and embedded deployment, image registration and warping, and translating fundamental research into production-grade systems while providing technical leadership., We are seeking a tenured Computer Vision Engineer to serve as a technical thought leader alongside our engineering leadership. In this role, you will bridge advanced R&D with production engineering to solve some of the toughest, unsolved computer vision problems in complex retail environments., * Design, implement, and optimize state-of-the-art deep learning, computer vision, and visual-language models (VLMs) for real-world retail edge deployments.

  • Bridge exploratory research and production code, executing data-backed analysis to validate algorithm performance against real-world engineering risks.
  • Optimize neural network inference for high-throughput, low-latency execution using TensorRT and custom CUDA primitives.
  • Containerize and deploy robust ML pipelines using Docker across cloud and edge/embedded environments.
  • Embrace modern AI-assisted workflows (Copilot, code-assisted tooling) to maximize engineering throughput and team productivity.

Requirements

This role requires a combination of rigorous academic grounding (deep research experience/publishing) and battle-tested industry execution. You will spend roughly 50% of your time on hypothesis-driven R&D and evidence-based analysis and 50% on concrete implementation, model optimization, and edge deployment., * 8+ years of substantial industry experience delivering production-grade computer vision systems, paired with strong academic/research experience (Master’s or Ph.D. level work in CS, Robotics, Electrical/Computer Engineering, or a related field).

  • Proven history of taking complex R&D/fundamental research and translating it into evidence-backed, production-grade pipelines.
  • Deep expertise in PyTorch, custom deep learning/graphics architectures, and Vision-Language Models (VLMs).
  • Hands-on experience with TensorRT, CUDA optimization, and low-level GPU acceleration.
  • Deep familiarity with Docker for reproducible ML environments.
  • Production-grade Python mastery; strong C++ capability for high-performance components.
  • Experience with dense image registration/warping algorithms.
  • Proven structured analytical approach to innovating in computer vision

Benefits & conditions

Augmodo offers benefits inclusive of medical, dental, vision, and 401k. The salary range for this role is $170,000 USD - $200,000 USD +equity

About the company

Augmodo is at the forefront of spatial computing, where mapping connects the digital and physical worlds. We build real-time spatial systems that give brick-and-mortar retail unprecedented physical intelligence.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on jobs.ashbyhq.com
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

3:16 min

Composing real time video flow applications utilizing multiple AI models

Ankit Patel Ankit Patel · World Congress 2024

4:52 min

Essential phases in building and refining language models

Anshul Jindal Anshul Jindal +1 · World Congress 2025

2:35 min

Preventing remote code execution in PyTorch models

Balázs Kiss · World Congress 2023

2:07 min

Inspecting default bridge architectures and custom Docker networks

Oliver Seitz Oliver Seitz · World Congress 2025

2:33 min

Architecting CUDA and the AI software stack

Michael Kagan Michael Kagan +1 · World Congress 2026 Europe

2:32 min

Core libraries driving inference engines and multi-GPU networking

Adolf Hohl Adolf Hohl · World Congress 2024

Videos

See all

Related articles

See all