AI / Machine Learning Engineer

1Kosmos•Iselin, NJ

3d•Hybrid

About The Position

1Kosmos is looking for an AI / Machine Learning Engineer to design, build, and deploy advanced computer vision and AI solutions. This role involves working on projects related to image capture, data extraction, and fraud detection, with the goal of delivering high-performance models suitable for both mobile devices and cloud environments. The position combines research and development with production engineering, requiring ownership of the entire ML lifecycle, from dataset creation and model training to deployment and performance optimization.

Requirements

Bachelor’s or Master’s degree in Computer Science, AI/ML, or related field (or equivalent experience).
3+ years of experience building and deploying ML models in production.
Proficiency in Python and ML frameworks (PyTorch, TensorFlow, or similar).
Experience with computer vision libraries (e.g., OpenCV) and OCR technologies.
Strong understanding of deep learning architectures for image and text recognition.
Familiarity with cloud platforms (AWS, GCP, or Azure) and API development.
Strong problem-solving skills and ability to work in fast-paced environments.

Nice To Haves

Experience with model quantization and optimization for mobile deployment.
Knowledge of synthetic data generation and data augmentation techniques.
Background in security, liveness detection, or anomaly detection.
Exposure to compliance and data privacy regulations (GDPR, CCPA).
Contributions to open-source ML projects or published research.

Responsibilities

Design and implement AI models for image classification, object detection, OCR, and feature extraction.
Develop real-time image quality assessment and capture guidance algorithms.
Create and maintain data pipelines for collecting, cleaning, augmenting, and labeling datasets.
Implement model optimization techniques for mobile (on-device) and cloud inference.
Apply fraud detection methods to identify tampering, forgeries, or replay attacks in visual data.
Integrate ML models into production-grade APIs and mobile SDKs.
Monitor, evaluate, and continuously improve model accuracy and performance.
Collaborate with product and engineering teams to align AI capabilities with business goals.