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.
Minimum Qualifications :
Master's or Ph.D. in Computer Science, Electrical Engineering, or a related field.5+ years of experience computer vision, machine learning, or biometrics.TS Clearance or CBP ClearanceProven 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.Preferred Qualifications
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 practicesPrior experience with managing enterprise systems and knowledge of CBP enterprise system tools and processes is preferred.