Senior Manager, Machine Learning

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The salary range for this position takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs.

At WGU, it is not typical for an individual to be hired at or near the top of the range for their position, and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is:

Job Description

Job Profile Summary

The Senior Manager, Machine Learning is a champion of Machine Learning innovation. This manager believes in the power of technology and has built broad and significant leadership skills in the AI/ML field. Driven to create a collaborative environment, this manager transforms opportunities into solutions. Adaptable in working efficiently towards team and department goals and reliable in understanding technical concepts. As an effective team leader and department advocate, this manager enjoys inspiring and developing others and leads the work and people across multi-functional teams and departmental environments. Demonstrates confidence, enthusiasm and enjoys inspiring and developing others through direct and indirect leadership. This position focuses on strategic and operational priorities.

Essential Functions and Responsibilities:

• Leads a team and department of ML Engineers for the organization through direct and indirect report leadership.

• Participates in Applied ML strategy development and operationalization of approved strategies and initiatives.

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

• Manages and applies continues improvement approaches to 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 in new and undefined business areas.

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

• Uses and interprets complex data to develop solutions and outcomes.

• Collaborates frequently with a large number of cross-functional and internal/external partners to provide expertise in building and applying ML models.

• Provides technical and strategic guidance and mentorship to internal stakeholders.

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

• Actively participates in defining and executing a multi-year strategic technical roadmap.

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

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

• Leads complex 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 and recommends 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.

Competencies:

Organizational Impact:

• Manages a team that focuses on executing the operational plans for the job area with measurable contribution to the achievement of results of the department, function, or office.

• Assigns and distributes work.

• Compiles data to prepare budgets.

Problem Solving and Decision Making:

• Responsible for making moderate improvements of processes or systems to enhance performance of the job area.

• Assignments received and problems faced are broad and undefined, and occasionally require use of analytical concepts, investigation, and knowledge from prior experience.

Communication and Influence:

• Communicates within job area and occasionally with external groups. External facing professionals (i.e. Admissions) communicate more regularly with external groups on routine matters.

• Ensures compliance with university policies and procedures within job area and may influence others outside of job area to justify and gain cooperation for policies, practices, and procedures.

Leadership and Talent Management:

• Manages/Supervises a team of professionals. Manages the work of assigned employees and/or supervisors who generally exercise some latitude and independence in their assignments. Ensures proper training of team members, and participates in hiring, firing, and promotion decisions. Conducts performance reviews and may recommend salary reviews.

• May complete assignments that are technical in manner in addition to supervising others.

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.

• 7+ 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.

• 4+ 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.

• Strong communication skills, with attention to detail and ability to convey rigorous technical concepts and considerations to non-experts, both verbally and in written format.

• Comfortable working in a fast paced, highly collaborative, dynamic work environment

• 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.

• Excellent critical thinking, planning, prioritization, and organization skills.

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

• Experience with Databricks preferred.

• Experience with cloud platforms, preferably AWS.

Position & Application Details

How to Apply: If interested, an application will need to be submitted online. Internal WGU employees will need to apply through the internal job board in Workday.

Additional Information

Disclaimer: The job posting highlights the most critical responsibilities and requirements of the job. It's not all-inclusive.

Accommodations: Applicants with disabilities who require assistance or accommodation during the application or interview process should contact our Talent Acquisition team at recruiting@wgu.edu.

Equal Employment Opportunity: All qualified applicants will receive consideration for employment without regard to any protected characteristic as required by law.