AI / Machine Learning Engineer
Indexed description
The ideal candidate will have strong experience developing production-grade machine learning models, working across the full ML lifecycle—from data preparation and model development to deployment and optimization across cloud and mobile environments.
Key Responsibilities:
- Design and develop AI/ML models for computer vision, image classification, object detection, OCR, and feature extraction
- Build real-time image quality assessment, data processing, and intelligent capture solutions
- Develop and maintain data pipelines for data collection, labeling, cleaning, and augmentation
- Optimize ML models for cloud and mobile/on-device inference
- Implement fraud detection, anomaly detection, and security-focused AI capabilities
- Integrate ML models into production APIs and software platforms
- Monitor model performance and continuously improve accuracy and scalability
- Collaborate with engineering, product, and business teams to deliver AI-driven solutions
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or related field (or equivalent experience)
- 3+ years of experience building and deploying machine learning models in production environments
- Strong proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or similar
- Experience with computer vision libraries (OpenCV) and OCR technologies
- Strong understanding of deep learning architectures for image and text recognition
- Experience with cloud platforms such as AWS, Azure, or GCP
- Strong problem-solving skills and ability to thrive in a fast-paced environment
- Experience with model optimization and quantization for mobile deployment
- Knowledge of synthetic data generation and data augmentation techniques
- Background in fraud detection, anomaly detection, security, or identity technologies
- Familiarity with data privacy and compliance standards
- Experience contributing to open-source projects or AI research
- Build next-generation AI capabilities with real-world enterprise impact
- Work on innovative computer vision and machine learning challenges
- Partner with talented engineering teams to move AI solutions from research to production
- Drive improvements in accuracy, performance, and scalability
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