Senior Software Engineer, Computer Vision
New
United States, multiple time zonesFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5+ years
- Required Skills
- DockerPostgreSQLPythonOpenCVFastAPIDeep LearningMLOpsComputer Vision
Requirements
- 5+ years of professional experience in computer vision, object detection, and AI-driven image processing systems.
- Strong hands-on experience training and fine-tuning deep learning models for real-world production environments.
- Expertise in Python development with strong knowledge of OpenCV, image preprocessing, augmentation, and OCR pipelines.
- Experience working with multimodal LLM/LVM APIs for structured data extraction and validation workflows.
- Solid backend engineering experience using FastAPI, Pydantic v2, PostgreSQL, and asynchronous Python development.
- Familiarity with barcode, QR code, or UDI decoding technologies and preprocessing optimization techniques.
- Experience with MLOps practices, including Docker, CI/CD pipelines, model versioning, and A/B testing, is a plus.
- Exposure to workflow orchestration tools such as Temporal, Prefect, or Airflow is beneficial.
- Healthcare, medical device, or supply chain technology experience is highly valued.
- Strong analytical thinking, problem-solving abilities, and attention to detail in high-accuracy production environments.
Responsibilities
- Design, develop, and optimize multi-stage computer vision pipelines involving object detection, segmentation, OCR, barcode decoding, multimodal LLM/LVM extraction, and data reconciliation.
- Train, fine-tune, and improve computer vision models using custom datasets, synthetic data generation, and advanced augmentation techniques.
- Build and maintain scalable backend services using asynchronous Python frameworks to support downstream operational and clinical workflows.
- Monitor pipeline accuracy and performance by implementing field-level metrics, analyzing failure modes, and continuously improving precision and recall.
- Develop auditable persistence schemas and structured data models that ensure transparency and traceability across all extraction processes.
- Collaborate cross-functionally to integrate AI-driven image analysis solutions into production systems with high reliability and operational accuracy.
- Contribute to architecture decisions, deployment strategies, and continuous improvements across AI and backend infrastructure.
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