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Current WGU employees should submit an internal application before 3/24/2023 to be considered.

The Manger, Applied Machine Learning is a champion of Machine Learning innovation. This manager believes in the power of technology and has built leadership skills in the AI/ML field. Driven to create a collaborative environment, this manager transforms opportunities into solutions. Adaptable in working efficiently towards goals and reliable in understanding technical concepts. As an effective Team leader, this manager enjoys inspiring and developing others and works well as part of a multi-functional team. Demonstrates confidence, enthusiasm and enjoys inspiring and developing others.

Essential Functions and Responsibilities:

• Leads as an hands-on leader for Applied ML and Research for the organization.

• Hires and builds a team of scientists and leads them to design, develop, and evaluate innovative ML models to solve diverse challenges and opportunities.

• Manages customized machine learning applications to drive innovation and optimizes business values

• Leads with cultivating a strong applied science and engineering culture, responsible for delivering business results.

• Works closely with our Analytics and MLOps teams to drive model implementations and new algorithms.

• Works closely with a large number of cross-functional partners to provide expertise in building and applying ML models.

• Provides technical guidance and mentorship to internal stakeholders.

• Builds the capabilities for measuring and improving quality of machine learning models.

• Defines and executes a multi-year technical roadmap.

• Supports and develops talent, identifying goals for each team member to grow and contribute to their full potential.

• Communicates with executives and team leaders; drives the strategy of ML innovation.

• Leads technical discussions, providing domain expertise and strategic influence.

• Communicates research and development results to internal and external audiences in oral and written form.

• Collaborates with product groups and other stakeholders to deploy research and development solutions at scale.

• Researches ways to improve models, increase adoption and value.

• Validates other member's ML work and evaluate models for pitfalls.

• Supports and executes A/B tests and experiments.

• Investigates trends and needs for ML models.

• Partners with other teams to make insights and models results actionable.

Job Qualifications:

Minimum Qualifications:

• M.S. and PhD in data science, computer science, engineering, mathematics, physics or related technical/scientific field.

• 7+ years of professional experience in a business environment.

• 5+ years of relevant experience in building large scale machine learning or deep learning models on cloud platform, carrying out cutting-edge research into product innovation.

• 3+ years of experience leading and managing scientists and engineers.

• Excellent research skills with the ability to break long term research goals into achievable milestones. Ability to clearly articulate the problems and explore related solutions.

• Sound theoretical understanding of broad machine learning concepts, with deep and demonstrable expertise in at least one topic or application of machine learning.

• Strong coding and problem-solving skills in Python and other programming languages.

• Practical experience in solving complex problems in an applied environment.

• Hands on experience building models with deep learning frameworks like Tensorflow, PyTorch, etc.

• Scientific thinking and the ability to invent, a track record of thought leadership and contributions that have advanced the field.

• Successful record of developing junior scientists to a successful career track.

• Ability to establish strong partnerships and manage complex cross-functional relationships and projects.

• Experience with Databricks preferred.

• Experience with cloud platforms, preferably AWS.

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As an equal opportunity employer, WGU recognizes that our strength lies in our people. We are committed to diversity.