Computer Vision Engineer (Hybrid :: W2 Only)

Experience

• 3 5 years of hands-on experience building computer vision and machine learning models.
• Proven track record taking models from experimentation to production.

Skills

• Proficiency in both modern AI-based CV models (CNNs, transformers, embeddings) and traditional computer vision
• Strong Python skills for CV/ML development, data processing, and experimentation.
• Experience with PyTorch or TensorFlow.
• Hands-on experience with detection, segmentation, classification, and image/video analysis.
• Practical knowledge of computer vision hardware-cameras, sensors, lighting, and edge devices-and the real-world constraints that affect data quality and model performance.
• Experience with broader ML problems: time-series modeling, anomaly detection, clustering, and data analysis.

Abilities

• Strong analytical and performance-debugging skills.
• Able to evaluate model options and turn business problems into practical AI solutions.
• Strong problem-solving skills and ability to work in a fast-paced, agile environment.

Education:

• Bachelor's or Master's degree in Computer Science, Engineering or a related field.

Preferred Qualifications

• Experience deploying models to edge devices or optimizing for inference (quantization, pruning, TensorRT, ONNX).
• Familiarity with MLOps practices: experiment tracking, model versioning, and drift/performance monitoring.
• Experience with cloud platforms (Azure, AWS, or Google Cloud Platform) and GPU-based training.
• Experience working with retail, IoT, or real-world imaging datasets.