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Job Description

We are seeking a SME Biometrics Engineer to join our clients innovative team in Ashburn, VA. This is a hybrid position with two days onsite and three days remote. In this role, you will lead the development and integration of cutting-edge biometric recognition systems powered by artificial intelligence. Responsibilities include:

-Lead the design and implementation of advanced AI-driven biometric recognition systems (e.g., facial, fingerprint, iris) for high-security, large-scale applications.

-Develop and implement cutting-edge algorithms for computer vision tasks, including object detection, tracking, segmentation, and re-identification and conduct research on emerging methods, algorithms, and industry trends, translating findings into practical applications.

-Architect and implement pipelines for ingesting, processing, and fusing data from various biometric modalities (e.g., facial recognition, fingerprint, voice) and develop and deploy predictive models (e.g., classification, clustering, deep learning methods) leveraging integrated biometric and other relevant data.

-Design and implement Approximate Nearest Neighbor (ANN) algorithms such as Hierarchical Navigable Small World (HNSW), Locality-Sensitive Hashing (LSH), Faiss, or Annoy to optimize large-scale similarity search and optimize model performance and scalability for real-time or near real-time predictive applications.

-Lead the development of novel evaluation metrics and benchmark datasets to rigorously test and validate algorithm performance and collaborate with cross-functional teams to integrate biometric technologies into secure, scalable, and efficient system architectures and document system designs, processes, and research findings for internal knowledge sharing, audits, and external stakeholders.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to [email protected] learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.

Skills and Requirements

-Active Top Secret Clearance and ability to obtain public trust

-Master’s or Ph.D. in Computer Science, Electrical Engineering, or a related field.

-5+ years of experience computer vision, machine learning, or biometrics.

-Proven expertise in biometric recognition modalities such as face, iris, fingerprint, or voice and solid understanding of image processing, segmentation, object detection, and feature engineering.

-Strong knowledge of approximate nearest neighbor (ANN) search algorithms and libraries (HNSWm FAISS, Annoy) and proficiency in deep learning frameworks (PyTorch, TensorFlow, Keras).

-Strong programming skills in Python, C++, or Java with emphasis on performance optimization. -Experience in scalable biometric matching systems with millions of identities.

-Publications or patents in computer vision/biometric recognition.

-Hands-on experience with cloud computing environments (AWS, Azure, or GCP) and designing scalable, secure software architectures and strong understanding of data security, privacy, and compliance requirements in biometric applications, including relevant standards and best practices

-Prior experience with managing enterprise systems and knowledge of CBP enterprise system tools and processes is preferred.