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Generative AI and ML Product Operations Program Manager, Support Apps
Altus, OK
·
On-site
·
Full-time
·
1mo ago
Benefits & Perks
•Wellness benefits
•Remote work flexibility
•Parental leave program
•Learning and development stipend
•Annual team offsites
•Health, dental, and vision coverage
Required Skills
Airflow
Python
TensorFlow
Generative AI and ML Product Operations Program Manager, Support Apps
3 weeks ago• Altus, OK
Apply on company site
About Us
Working at Apple means doing more than you ever thought possible and having more impact than you ever imagined.
Size: 10000+ employees
Industry: Technology, Information Technology, Software, Consumer Goods & Services
Apple Care Digital brings the highest standard of quality and innovation to Apple customers around the globe across a broad range of digital experiences. The organization is responsible for support and service experiences that span content, web assets, customer tools and apps, community forums, analytics, SEO, and social media.
Join the Digital Product Ops team which leads customer experience improvements for two of Apple's most impactful digital properties - the Apple Support App and the 'Get Support' web app (getsupport.apple.com) which impact millions of customers every day. We help customers describe and solve support problems with digital content and video; we also connect customers with assisted support options like the Genius Bar and phone and chat advisors. At our core, we create experiences that seamlessly help customers use and love their Apple products.
The AI/ML Product Ops Program Manager ensures that the machine learning models we use to make our customer experience better are truly useful, accurate, and responsibly integrated into our customer facing platforms and backend systems. In this role, you will develop a solid understanding of the team's existing technical implementations and operational processes, and use that knowledge, alongside data-driven insights and systems thinking, to create informed improvements to our customer experience, product platforms or backend services, for impactful and trustworthy and scalable AI-driven experiences.
We are seeking an individual who can work independently and also thrives working on a collaborative team and is ready to roll up their sleeves to get things done. The ideal candidate will need to be well versed in both organizational strategy and technical product capabilities so they can transform customer and business problems into actionable solutions. We are looking for someone who has a vision for the future and is excited about leading and participating in ideation sessions.
Description:
As the ML Product Operations Program Manager, you will be partnering with the technical product managers, engineers, solution architects, ML analysts, data scientists and others to translate generative AI and ML feature ideas into efficient systems, scalable tools, and delightful customer experiences.
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","responsibilities":"Champion system design for new features including collaborating closely with product managers and engineers to translate complex AI/ML capabilities into intuitive, user-friendly configuration and business analyst capabilities.
Prioritize product features by balancing user impact, technical feasibility, and readiness, effectively translating ambiguous ML goals into clear user problems and actionable product requirements.
Work to integrate and optimize ML functionality with established systems to ensure data quality, feature availability, and feedback loops are in place.
Develop and manage comprehensive program roadmaps, defining clear objectives, key results, milestones, and dependencies for ML integration projects, proactively identifying and mitigating risks to ensure on-time and high-quality delivery.
Facilitate effective communication and stakeholder alignment by providing regular, transparent updates on program status, challenges, and successes to executive leadership and various internal teams, fostering strong partnerships and informed decision-making.
Influence continuous improvement through data and feedback by providing robust mechanisms for collecting, analyzing, and acting upon user feedback and performance metrics specific to ML-driven features; Partnering closely with product and cross-functional program teams to inform model refinement and future product enhancements.
Collaborate with Data Science and Engineering teams on the ML model lifecycle, ensuring efficient processes for data collection, model training, performance evaluation, deployment, and robust monitoring.
Preferred Qualifications:
MBA a plus
Knowledgable in SQL, R/Python
Proven success leading programs that span ML and/or digital support channels (chat, self-service) or contact center/IVR systems.
Experience building AI-powered support solutions (e.g., virtual agents, chatbots, predictive routing).
Understanding of agile and design thinking methodologies
Minimum Qualifications:
Bachelors in Engineering, Computer Science or similar field of study with 8 years of applicable experience, or a Master's degree in a similar field with 6 years of applicable experience
4-6 years of program management experience including program strategy, process definition, planning, execution, risk management, and resource allocation, while managing multiple work streams interdependently
Demonstrated data-driven decision-making skills, including experience leading metrics-driven projects or programs
Experience with tools like Tableau to measure KPI's (CSAT, customer effort, self service adoption, abandon rate, etc.)
Strong understanding of the machine learning development lifecycle (MLOps), including data pipelines, model training, evaluation, deployment, and monitoring, to effectively guide technical discussions.
Proficient in applying Agile/Scrum principles to manage dynamic product development cycles, particularly in environments integrating cutting-edge ML technologies, prompt management systems and LLM evaluation
Excellent written and verbal communication skills, capable of articulating technical concepts to non-technical audiences. Able to independently draft and present deliverables, recommendations, timelines, status updates and communication strategies to executives
Able to lead, partner and drive consensus with product, UX/UI, engineering and other cross functional partners to translate ML capabilities into product features and user experiences
Strong understanding of how backend configuration tools and ML model deployment systems are designed and managed. Ability to influence the architecture and usability of these internal tools to ensure they effectively enable agile iteration, robust control, and optimal user experience for ML-powered features.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .
Client-provided location(s): Altus, OK
Job ID: apple-200625349-0240_rxr-660
Employment Type: OTHER
Posted: 2026-01-07T19:12:55
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Parental Benefits
Work Flexibility
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About Apple

Apple
PublicA technology company that designs, manufactures, and markets consumer electronics, personal computers, and software.
10,001+
Employees
Cupertino
Headquarters
$3.5T
Valuation
Reviews
4.0
10 reviews
Work Life Balance
4.0
Compensation
4.2
Culture
3.8
Career
3.5
Management
3.2
75%
Recommend to a Friend
Pros
Great coworkers and people
Excellent benefits and perks
Fast-paced and engaging work environment
Cons
High expectations and pressure
Management quality varies
Limited career progression opportunities
Salary Ranges
17,968 data points
L2
L3
L4
L5
L6
L2 · Business Analyst L2
0 reports
$114,215
total / year
Base
$45,686
Stock
$57,108
Bonus
$11,422
$79,951
$148,480
Interview Experience
5 interviews
Difficulty
3.4
/ 5
Duration
28-42 weeks
Offer Rate
20%
Experience
Positive 20%
Neutral 40%
Negative 40%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Behavioral Interview
5
Onsite/Virtual Interviews
6
Team Matching
7
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Culture Fit
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