Principal Applied Scientist

Found in: Jooble US O C2 - 2 weeks ago

Seattle WA, United States MissionStaff Full time

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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