Artificial Intelligence Developer
Position Type: Hybrid
Hybrid Schedule: Onsite one week a month
Contract Length: 8 months + possible extensions
Position Overview:
We are seeking a Machine Learning Vision Engineer to design and implement advanced OCR and computer vision solutions that power large-scale, real-time image-based transaction processing. This role blends software engineering best practices with applied ML to deliver scalable, production-ready systems that integrate seamlessly into distributed architectures.
Duties:
Design, implement, and optimize ML-based computer vision components, including object detection, image classification, OCR pipelines, and image quality assessment classifiers.
Develop robust, production-ready Python code leveraging Object Oriented Design (OOD) principles.
Collaborate with system architects to integrate ML components into distributed, message-driven architectures.
Implement training, evaluation, and feedback loops for OCR and image classifiers.
Optimize models for performance in near real-time transaction workflows with low latency and high throughput.
Participate in system-level design discussions to ensure scalability, maintainability, and adaptability.
Work closely with database, API, and DevOps teams for smooth deployment and testing.
Build frameworks and systems suitable for production, beyond proof-of-concept work.
Fully document technical and functional designs, test plans, impact analysis, lessons learned, and best practices.
Develop and maintain productive relationships with technical teams, business stakeholders, vendors, and clients.
Lead and participate in project team activities related to enterprise system enhancements.
Work independently to complete assigned tasks and responsibilities.
Adhere to organizational standards, policies, and procedures.
Utilize various software and technology tools as needed for job duties.
Perform other related duties as assigned.
Required Skills:
Strong professional experience with Python (must be clearly demonstrated in resume).
Solid background in software engineering: Object Oriented Programming (OOP), design patterns, clean code, and testable architectures.
Experience with image processing and computer vision frameworks (e.g., OpenCV, Pillow).
Hands-on experience with machine learning frameworks (e.g., PyTorch, TensorFlow).
OCR-related experience (such as Tesseract, PaddleOCR, EasyOCR, or custom models).
Familiarity with object detection frameworks (e.g., YOLO, Faster R-CNN, SSD).
Knowledge of classification, feature extraction, and evaluation metrics for vision tasks.
Proficient with Microsoft Office 365 suite (Teams, Word, Excel, PowerPoint) and Microsoft ADO Testing Module.
Bachelor’s degree in business management or information systems, or an equivalent combination of education and experience.