Fast Facts
WGU is seeking a Manager of Machine Learning Operations to lead a team focused on MLOps solutions, ensuring timely and quality delivery of machine learning applications. This role combines technical leadership with team development and collaboration across various departments.
Responsibilities: Manage a team of MLOps Engineers, oversee the development of MLOps solutions, ensure compliance with ML standards, and drive cross-team collaboration on projects.
Skills: Expertise in MLOps, Agile methodologies (SCRUM, TDD), strong coding skills in Python, and experience with ML model management platforms are required.
Qualifications: A B.S. and M.S. in Computer Science, Data Science, or related field, along with significant experience in software engineering, MLOps architecture, and team management are preferred.
Location: This position is based in North Carolina, USA, and is a full-time regular position.
Compensation: $170400 - $281200 / Annually
If you’re passionate about building a better future for individuals, communities, and our country—and you’re committed to working hard to play your part in building that future—consider WGU as the next step in your career.
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 715Pay 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 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:
- B.S. and M.S. degree in Computer Science, Software Engineering, Data Science, Machine Learning, Math, Physics, or related field.
- 7+ years of Software Engineering, Data Science or Machine Learning experience.
- 5+ years of experience working in an AI / ML context alongside Data Scientists or ML Engineers.
- 5+ years of experience with building MLOps pipelines and processes (CI/Cd and CT) in cloud architecture (preferably Databricks).
- Ability to understand and clearly articulate trade-offs of various approaches to solving machine learning platform problems.
- Fluency in Python and demonstrable history of writing clean, clear code as part of a team.
- Experience with ML model management platforms, like MLFlow or Sagemaker.
- Experience with production model validation techniques.
- Experience with creating recommended systems.
- Significant, hands-on experience supporting large datasets.
- 2+ years of experience leading an MLOps team.
- 2+ years of experience managing projects from end-to-end.
- 5+ years of experience working in collaboration with business and other teams.
- Business acumen and understanding.
Preferred Qualifications:
Physical Requirements:
- Prolonged periods sitting at a desk and working on a computer.
- Must be able to lift up to 15 pounds at times.
Position & Application Details
Full-Time Regular Positions (classified as regular and working 40 standard weekly hours): This is a full-time, regular position (classified for 40 standard weekly hours) that is eligible for bonuses; medical, dental, vision, telehealth and mental healthcare; health savings account and flexible spending account; basic and voluntary life insurance; disability coverage; accident, critical illness and hospital indemnity supplemental coverages; legal and identity theft coverage; retirement savings plan; wellbeing program; discounted WGU tuition; and flexible paid time off for rest and relaxation with no need for accrual, flexible paid sick time with no need for accrual, 11 paid holidays, and other paid leaves, including up to 12 weeks of parental leave.
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.
