MissionStaff
Principal Applied Scientist - AI & Deep Learning
MissionStaff, Seattle, Washington, us, 98127
Join our clients Seattle-based R&D team as a Principal Applied Scientist, specializing in AI and deep learning. In this role, you'll spearhead the development and deployment of AI models, deep learning solutions, and industry-leading techniques for challenges such as identity verification, fraud detection, background checks, and risk management. Lead a dynamic team of scientists and engineers, and be the innovative force behind the platform's enhanced accuracy and efficiency.
Your Key Responsibilities
Oversee the R&D of advanced AI and deep learning models, targeting the nuanced intricacies of fraud detection, risk analysis, and identity verification.Engage directly with the CTO, and work alongside cross-disciplinary teams to crystallize project aims, prerequisites, and outcomes.Utilize sophisticated machine learning strategies to dissect extensive, intricate datasets, uncovering crucial insights and refining predictive models that upgrade our risk, background, and identity verification protocols.Craft and deploy leading-edge algorithms for tasks like entity differentiation, graph database analysis, and search/data retrieval.Stay abreast with the newest trends in AI, machine learning, and deep learning. Incorporate these novel methods to uplift our model and system performance.Offer expert mentorship to budding team members, cultivating a spirit of cooperation and ingenuity.Partner with product and business units, transforming client needs into scalable and dependable AI solutions.Disseminate research discoveries, project milestones, and tech advancements to both internal teams and leadership.Prioritize unsupervised and semi-supervised learning models in addition to supervised learning paradigms.Your Qualifications
Education: A Ph.D. in Computer Science, AI, or a similar domain, emphasizing deep learning, reinforcement learning, and graph neural networks. Extensive professional experience in the sector is equally valued.Experience: At least 6-10 years in AI applied research, concentrating on deep learning, reinforcement learning, and graph neural networks. A history of guiding successful initiatives and teams.Technical Mastery: Proficient in programming languages such as Python or C++, with a command over AI toolkits like TensorFlow, Keras, or PyTorch. Comprehensive understanding of deep learning structures.Leadership: Proven ability to galvanize and direct a team of scientists and engineers. Robust project management expertise.Communication: Stellar communication capabilities, apt at explaining intricate tech details to varied audiences. A record of research presentation at elite conferences and publications.Innovation: A penchant for thinking out-of-the-box, pioneering new solutions, and propelling the AI research frontier.Problem-Solving: Exceptional analytical skills, capable of deconstructing complex issues and crafting trailblazing AI solutions.
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Your Key Responsibilities
Oversee the R&D of advanced AI and deep learning models, targeting the nuanced intricacies of fraud detection, risk analysis, and identity verification.Engage directly with the CTO, and work alongside cross-disciplinary teams to crystallize project aims, prerequisites, and outcomes.Utilize sophisticated machine learning strategies to dissect extensive, intricate datasets, uncovering crucial insights and refining predictive models that upgrade our risk, background, and identity verification protocols.Craft and deploy leading-edge algorithms for tasks like entity differentiation, graph database analysis, and search/data retrieval.Stay abreast with the newest trends in AI, machine learning, and deep learning. Incorporate these novel methods to uplift our model and system performance.Offer expert mentorship to budding team members, cultivating a spirit of cooperation and ingenuity.Partner with product and business units, transforming client needs into scalable and dependable AI solutions.Disseminate research discoveries, project milestones, and tech advancements to both internal teams and leadership.Prioritize unsupervised and semi-supervised learning models in addition to supervised learning paradigms.Your Qualifications
Education: A Ph.D. in Computer Science, AI, or a similar domain, emphasizing deep learning, reinforcement learning, and graph neural networks. Extensive professional experience in the sector is equally valued.Experience: At least 6-10 years in AI applied research, concentrating on deep learning, reinforcement learning, and graph neural networks. A history of guiding successful initiatives and teams.Technical Mastery: Proficient in programming languages such as Python or C++, with a command over AI toolkits like TensorFlow, Keras, or PyTorch. Comprehensive understanding of deep learning structures.Leadership: Proven ability to galvanize and direct a team of scientists and engineers. Robust project management expertise.Communication: Stellar communication capabilities, apt at explaining intricate tech details to varied audiences. A record of research presentation at elite conferences and publications.Innovation: A penchant for thinking out-of-the-box, pioneering new solutions, and propelling the AI research frontier.Problem-Solving: Exceptional analytical skills, capable of deconstructing complex issues and crafting trailblazing AI solutions.
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