Computer Vision Researcher / Developer

EAIGLE is a computer vision AI platform helping enterprises in supply chain and logistics turn vision data into security, transportation, and operational outcomes. Our solutions include
AVAC™, automated vehicle access control at the retailer's gate, and
YardSight™, real-time monitoring of loading docks and truck parking availability across the yard. The platform combines on-premise computer vision components with Azure cloud services, and is deployed today at Fortune 100 and 500 companies.
The RoleWe're looking for a Computer Vision Researcher to take AI solutions for image and video understanding from research through to production. You'll own problems end to end: framing them, experimenting, building and training models, evaluating rigorously, optimizing for real-world constraints, and shipping to cloud and edge environments.
This is a role for someone who is comfortable moving between a paper and a production incident in the same week, and who is willing to pick up whatever technology the problem requires.
What You'll Do
Research, adapt, and deploy state-of-the-art computer vision and deep learning methods for our products.
Design, train, fine‑tune, and evaluate models across detection, tracking, segmentation, OCR, and related vision tasks.
Build the data pipelines behind the models — collection, annotation, augmentation, and preprocessing at scale.
Optimize models for accuracy, latency, memory, and cost, and deploy them to cloud and edge environments.
Define evaluation metrics, benchmark rigorously, and monitor deployed models to drive the next iteration.
Document your findings and designs clearly, and contribute to publications, patents, or open source where it makes sense.
What We're Looking For
Master's or PhD in Computer Science, AI, Electrical Engineering, Mathematics, or a related technical field.
Substantial research or professional experience in computer vision and deep learning.
Depth in 3D camera geometry and motion.
This is central to what we do, and we want someone who has genuinely worked in this space — 3D tracking, structure from motion, visual SLAM, multi‑view geometry, camera calibration and pose estimation, stereo or depth estimation, or closely adjacent problems.
Strong Python skills, with hands‑on experience in PyTorch and/or TensorFlow and OpenCV.
Experience taking models from experiment to production.
Comfort working across Linux and Windows, with Git and modern engineering practices.
Strong analytical and communication skills, and the self‑direction to work through ambiguous problems.
Nice to Have
Experience with modern architectures and frameworks such as Vision Transformers, YOLO, SAM, CLIP, diffusion models, or vision‑language and multimodal systems.
Inference optimization and acceleration experience — quantization, pruning, distillation, ONNX, TensorRT, OpenVINO, CUDA.
Edge AI or embedded deployment experience.
Familiarity with Azure or another major cloud platform, and with MLOps tooling and ML pipelines.
Experience with containerized deployment with Docker
C++ alongside Python.
Publications at recognized vision or AI venues, or contributions to open‑source vision projects.
#J-18808-Ljbffr