Senior Director, Applied Science (Remote Work Option) ID-12497
<h2>Description</h2>
<p>Open to remote work except in South Dakota, Vermont and West Virginia.<br />
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The annual base salary for this position ranges from $199,200.00 in our lowest geographic market to $471,100.00 in our highest geographic market. Actual salary will vary based on a candidate's location, qualifications, skills and experience.<br />
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Information about benefits can be found here (https://jobs.nike.com/benefits) .<br />
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<strong>WHO WE ARE LOOKING FOR</strong><br />
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We are seeking a visionary leader to spearhead CPI’s Advanced Machine Learning initiatives, aimed at revolutionizing Nike’s product creation lifecycle—from ideation through to supply chain. This role requires a deep learning expert who is well-versed in generative AI advancements and capable of guiding cutting-edge research in these domains. This leader will build and develop the team, shape the science philosophy, plan, and strategize, as we explore domains such as Large Language Models (LLMs), diffusion models, reinforcement learning (RL) and simulation to support new experiences for our designers and developers.<br />
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<strong>WHAT YOU WILL WORK ON</strong><br />
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Design Acceleration: Al generated - Image and video generation, text and content creation to augment and enhance designer experience<br />
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ML Optimization: Adding LLM's to the existing data models to enhance accuracy of off the shelf GenAl solutions customized to Nike's data set and business needs.<br />
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<strong>WHO YOU WILL WORK WITH</strong><br />
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This role reports to the VP of Consumer Product and Innovation and will work closely with Product creation, Merch, Design, Innovation teams, and key partners across Footwear, Apparel, Ops, Merch and Geos.<br />
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<strong>WHAT YOU BRING</strong><br />
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+ Bachelor’s Degree in computer science, statistics, mathematics, software engineering, or related field (Master's or Ph.D. preferred).<br />
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+ Experienced leader of leaders, with 10 years of experience leading multiple science and engineering teams.<br />
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+ At least 15 years of experience in building and applying ML models to solve complex, large-scale problems.<br />
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+ Has a strong understanding of foundational models including large language models across multiple modalities, reinforcement learning, supervised learning, and other cutting-edge techniques in generative Al.<br />
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+ Proven track record of leading seasoned scientists and developing junior talent.<br />
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+ Proficient in one or more programming languages with strong technical skills.<br />
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+ Exceptional verbal and written communication skills, capable of advocating technical solutions to both technical and business audiences.<br />
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+ Publications in top-tier conferences or journals.</p>
