Senior Machine Learning Engineer
hace 3 semanas
About the role
About the job
This is a key role helping our product team as an applied scientist with a strategic mind and high research orientation, and first line of developing document anti-spoofing features. The ideal candidate will take ownership of document fraud R&D and be responsible for developing document anti-spoofing methods through all process stages until a new feature is deployed into the product.
Responsibilities
The successful candidate will be responsible for:
- Formulating innovative approaches to combat document fraud and reduce risk with the powers of Machine Learning.
- Creating new features, training new models, and deploying them into the production environment.
- Contributing to extending and improving our Machine Learning frameworks and platform, creating next-generation capabilities.
- Building and deploying solutions to interesting computer vision or Machine Learning problems, including document data extraction, fraud detection, or biometric verification challenges.
- Supporting and guiding other engineers in learning about, applying, and delivering product features driven by Machine Learning techniques.
- Working alongside other Machine Learning and computer vision specialists to deliver on both short-term objectives and long-term goals.
- Helping to develop robust model training and data infrastructure to support continual optimization of ML-driven approaches.
- Assisting in steering the ML-led development across the tech team.
- Gathering information about new tech trends from academic articles, journals, code repositories, and other relevant sources.
About you
The ideal candidate for this role will have a strong background in Machine Learning and computer vision, with a Ph.D. degree in Computer Science (or related quantitative field) or an MS degree in Computer Science with related experience. The candidate should have at least 5 years of experience building Machine Learning systems in production, with real-time technology problems. They should also have a strong academic and publication record, experience with cloud-based training and deployment pipelines, and excellent coding skills (Python is essential, C++ is considered a plus).
Requirements
The candidate should have proficiency with some of the following machine vision and machine learning frameworks: OpenCV, TensorFlow + Keras, TensorRT, PyTorch, PyTorch + FastAI. With a strong portfolio of development examples, Transformers management framework such as BERT is a plus. They should also have a good working knowledge of the tools in our dev stack, including Git, Google AI Cloud, Docker, and Kubernetes. A plus Linux, Redis, and ELK stack. Solid understanding of statistics, probability, linear algebra, and calculus. Hands-on experience working on computer vision and machine learning projects, such as face verification, object detection, and/or classification.
What we offer
We offer a competitive base salary, additional year-end bonus can be offered based on individual performance and company performance. We also provide learning days, where you can learn during working hours, and training budget for personal and team formation. A flexible working environment, currently fully remote due to COVID, but can be fully remote regardless for the right person. However, we do require you to be in our office from time to time if needed.
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