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# Computer Vision Machine Learning Engineer

- **Company:** Knightwerx Inc.
- **Location:** Scottsdale, AZ, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Airflow, Computer Vision, Machine Learning, Object Detection, Tensorflow, Pytorch, Deep Learning, Hardware Testing, Isaac Sim, Kubernetes, Information Technology, Data Management, Machine Learning Operations, NVIDIA Jetson
- **Published:** October 8, 2026
- **Apply:** https://www.disabledperson.com/jobs/75853784-computer-vision-machine-learning-engineer

## About the Role

* Bachelor's degree in Robotics, Computer Science, Electrical Engineering, or related field.
 * 2-5 years of relevant industry experience.
 * Strong C++ software development skills.
 * Experience with PyTorch, TensorFlow, or similar deep learning frameworks.
 * Strong understanding of classical and 3D computer vision principles.
 * Experience deploying machine learning models on edge hardware such as NVIDIA Jetson., * Master's or PhD in a related field.
 * ROS2 experience.
 * Services-oriented architecture experience.
 * Experience with the Isaac sim ecosystem.
 * Familiarity with Kubeflow, Airflow, Metaflow, or similar ML infrastructure tools.

## Description

* Build and own key perception infrastructure including video pipelines, data management systems, and training environments.
 * Design and implement real-time computer vision algorithms for high-resolution cameras, depth sensors, and multi-modal sensor inputs.
 * Develop object detection, image segmentation, depth estimation, and multi-object tracking capabilities.
 * Train, fine-tune, and evaluate machine learning models for scene understanding and 3D occupancy mapping.

Machine Learning and AI

 * Build scalable workflows for data collection, curation, labeling, and model training.
 * Optimize AI models for deployment on edge computing platforms.
 * Integrate perception outputs into autonomy, planning, and control systems.
 * Validate performance through simulation and real-world hardware testing.