AI Engineer - Computer Vision
About the role:
The Computer Vision Engineer role owns all computer vision engineering effort. You will work on edge-deployed CV pipelines running on NVIDIA Jetson hardware, and GPU servers — building, training, optimizing, and deploying models that handle real-world conditions in public and commercial spaces.
You will build systems with person and intent detection, multi-camera tracking, track package placement and removal events at shelf zones. You will also build model training and deployment pipelines and perform edge deployment and performance optimization.
Key responsibilities:
- Own all computer vision engineering efforts.
- Build, train, optimize, and deploy computer vision models for real-world conditions in public and commercial spaces.
- Develop edge-deployed CV pipelines running on NVIDIA Jetson hardware and GPU servers.
- Build systems for person detection and intent detection.
- Develop multi-camera tracking solutions.
- Track package placement and removal events within shelf zones.
- Build model training and deployment pipelines.
- Perform edge deployment and performance optimization of CV models and pipelines.
Required qualifications:
- 5+ years of hands-on computer vision engineering experience, with at least 2 years deploying models to production edge hardware (not just cloud or research environments)
- Deep practical experience with the YOLO family of detectors — training, fine-tuning, hyperparameter tuning, and understanding failure modes in real-world conditions
- Proficiency with PyTorch for model training and ONNX / TensorRT for inference optimization; hands-on experience with INT8 or FP16 post-training quantization
- Experience building multi-object tracking pipelines — SORT, DeepSORT, BoT-SORT, or equivalent — and understanding the tradeoffs between tracker accuracy, computational cost, and track stability
- Solid Python and C++ skills for pipeline development; comfort reading and modifying GStreamer pipeline graphs
- Experience with NVIDIA GPU tooling: CUDA, cuDNN, TensorRT, and the JetPack / Jetson SDK ecosystem
- Experience building annotation pipelines and managing training datasets for custom object detection tasks — not just using pre-trained models on standard benchmarks
- Comfort working with RTSP IP camera streams in Linux environments; understanding of H.264/H.265 codec pipeline and hardware decode
- Experience with cross-camera person re-identification — OSNet, FastReID, or equivalent architectures; homography-based multi-camera fusion
- Experience with zone-based spatial analytics — polygon intersection, floor-plane projection, homography calibration from camera to world coordinates.
- Experience building CV systems for retail, logistics, or security environments where the camera network covers a physical space and detections must be spatially anchored
- Familiarity with Roboflow or CVAT for dataset management and annotation workflow automation
- Experience with the NVIDIA Metropolis or DeepStream framework — even if ultimately not used, understanding where these add value vs a custom open-source stack
- Prior work on privacy-preserving CV pipelines — on-device inference, derived-data-only architectures, anonymization techniques
Compensation :
$80-$90/hr
This is the targeted compensation range for this role. Please note that this range is provided as a guideline and the final offer will be based on several factors, including but not limited to, skillset and competencies, level of experience, education, certifications, and location.
Benefits:
We offer a comprehensive benefits package including medical, dental, vision, life, and disability insurance; 401(k)
Work Authorization:
Work sponsorship is not available for this position. Applicants must be authorized to work in the United States without sponsorship.
Equal Employment Opportunity:
Zillion Technologies is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, national origin, age, disability, genetic information, veteran status, sexual orientation, gender identity, or any other characteristic protected by applicable federal, state, or local law.