Manager, Machine Learning Operations

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Driven by a mission to expand access to higher education through online, competency-based degree programs, WGU is also committed to being a great place to work for a diverse workforce of student-focused professionals. The university has pioneered a new way to learn in the 21st century, one that has received praise from academic, industry, government, and media leaders. Whatever your role, working for WGU gives you a part to play in helping students graduate, creating a better tomorrow for themselves and their families.

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:
 

Grade: Management Technical 715

Pay Range: $170,400.00 - $281,200.00

Job Description

The Manager, Machine Learning Operations will provide technical leadership, vision, direction, and mentoring for the Machine Learning Operations team. Manages a team of MLOps Engineers and Architects in building WGUs framework of MLOps solutions. Brings a service provider mindset leveraging Agile practices. Provides technical leadership and oversight of the development of integrated software algorithms to structure, analyze and leverage data in product and systems applications in both structured and unstructured environments. Selects, develops, and evaluates personnel ensuring the efficient operation of the function. Considers the end-user perspective and understands business concepts with a focus on impact and delivering quality work. Reports to the Senior Director of Data and Machine Learning. Collaborates closely with Research and Analytics teams.

 

Essential Functions and Responsibilities:

• Meets business needs by managing the activities of MLOps team in consistently delivering quality solutions on-time, within budget, and scope. Responsible for hiring, coaching, and developing talent within the team.
• Manages function operations and supervises employees, vendor resources and/or business support staff.
• Leads and manages solutions design, implementation, and execution of MLOps processes and integration with end-user applications.
• Creates standards and guidelines for ML and ensures compliance.
• Owns and manages enterprise MLOps platform operations.
• Manages ML models deployment as a product. Creates pipelines and roadmaps.
• Builds and fosters relationships with other teams and manages expectations accordingly.
• Presents and communicates results and status to various audiences.
• Performs other related duties as assigned.

Knowledge, Skill and Abilities:

• Strong people and management skills to interact with staff, colleagues, cross-functional teams and third parties.
• Commitment to quality through the ability to translate complex technical requirements into functional ML solutions using best practices.
• Expert in Agile methods including SCRUM and TDD.
• Excellent verbal and written communication skills and the ability to work equally well in self-managed and team-based Agile/Scrum projects.
• Experienced expert MLOps Engineer who has built MLOps architecture and pipelines in the past and aspires to become a leader in the field.

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 Univer