Top Computer Vision Jobs in Austin, TX

Lead design and productionization of egocentric and warehouse perception systems: data capture, camera rigs, calibration, multi-view 3D and pose estimation, automated labeling pipelines, model training/optimization, deployment, and establishing dataset quality standards for embodied AI.

Design and deploy physical AI and computer vision systems on factory production lines: specify cameras/lighting, integrate with PLCs and industrial networks, validate production performance, own customer technical relationships, and feed field insights back to product engineering.

Design, train, and deploy custom object-detection models for retail; fine-tune and integrate vision-language models; optimize models for edge devices; build dataset and annotation pipelines; prototype research ideas; and provide technical leadership and mentoring for CV infrastructure and production ML systems.

Design, train, and deploy production computer vision and vision-language models for retail product recognition. Optimize models for edge devices, build data pipelines and annotation workflows, fine-tune open-source VLMs, develop VLA pipelines, mentor engineers, and drive CV infrastructure and MLOps best practices.

Develop, optimize, and deploy production-grade computer vision models (depth, segmentation, tracking) for an autonomous mower. Own model lifecycle from data collection and synthetic-data strategies through training, edge optimization (quantization, mixed precision), and embedded NVIDIA GPU deployment. Integrate perception with robotics stack, analyze field failure cases, and continuously improve robustness for challenging outdoor conditions.

Review trainer-submitted image-question pairs and verify golden answers for accuracy and consistency. Flag and document incorrect, ambiguous, or incomplete responses, provide corrective feedback, track recurring errors, and escalate unclear cases. Ensure trainer output meets project quality standards.

Lead research, design, and production implementation of computer vision and ML solutions. Define architectures, run experiments, own model lifecycle (data, training, evaluation, deployment), optimize inference, set MLOps standards, mentor engineers, and collaborate with product and engineering teams to deliver production-quality CV features.

Design, implement, test, and maintain scalable C++ software for autonomous vehicle and perception systems. Work across full SDLC, support vehicle testing, simulation-based regression, data acquisition/analysis from remote vehicles, root-cause analysis, and mentor engineers while collaborating with ML researchers and cross-functional teams.

Lead design and implementation of computer vision systems for mapping, localization, image analysis, and 3D reconstruction on construction site data. Develop and optimize SLAM/SfM/VIO, deep learning perception models, and multi-modal approaches. Prototype, test, oversee datasets and collaborate with platform engineers to productionize scalable, robust solutions.

Lead development of orthomosaic tile imagery products for FireSat and SBEM: design and implement scalable mosaicking, orthorectification, and radiometric normalization algorithms; write production-ready code; author technical and customer-facing documentation; validate scientific quality; engage stakeholders and act as product owner for SBEM granule product; collaborate with engineers and scientists.