As a Machine Learning Engineer IV, you will have the opportunity to significantly impact the security and user experience of our ID verification solutions. Your expertise in deep learning and computer vision will drive the development of innovative algorithms that keep products at the forefront of the industry. By deploying and maintaining these models in production, you will ensure the robustness and reliability of our solutions, supporting our clients across diverse industries such as financial services, travel, the sharing economy, fintech, and gaming. Your contributions will be pivotal in maintaining product reputation as the leading provider of online identity verification solutions, helping to meet the growing demand for secure and seamless user verification globally.
Responsibilities:
- Develop, maintain, and own key fraudulent CV models, which shape the whole fraud product offering.
- Design and implement machine learning, deep learning, and classical CV focused on fraud detection. Research to support the deployment of the advanced algorithms.
- Deploy models as AWS SageMaker endpoints or directly onto devices.
- Stay updated with the latest advancements in machine learning, deep learning, and computer vision by engaging with academic papers and attending industry conferences.
- Work collaboratively with other engineers and product managers in an Agile development environment.
Requirements:
- Bachelor's or master's degree in computer science, data science, machine learning, or a related field.
- A minimum of 6+ years of commercial experience in the field of machine learning/deep learning, not including time spent studying (2 years with a master's).
- Must have: experience with training of DL models for deepfakes, synthetic data, or gen AI data detection.
- Deep understanding of how to convert ML metrics to product goals.
- Hands-on experience with PyTorch or TensorFlow, SKLearn, and developing production-grade Python code.
- Demonstrated experience in implementing best practices for monitoring and maintaining ML models in production environments.
- Strong communication and problem-solving skills.
Great to have:
- Experience in working with LLMs or VL Ms.
- Work with image or video generation.
- Experience with cloud environments: AWS/GCP.
- Experience in working in global organizations across several time zones.

