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About This Role
We are UMG, the Universal Music Group. We are the world’s leading music company. In everything we do, we are committed to artistry, innovation and entrepreneurship. We own and operate a broad array of businesses engaged in recorded music, music publishing, merchandising, and audiovisual content in more than 60 countries. We identify and develop recording artists and songwriters, and we produce, distribute and promote the most critically acclaimed and commercially successful music to delight and entertain fans around the world.
Famehouse, a division of UMG, is the preeminent leader in merchandise & D2C solutions in music, defining & delivering the industry’s best-in-class service to connect artists with their fans. Established & headquartered in Philly, Famehouse powers merch and D2C for UMG’s labels, artists, and Bravado. Our success & culture is fueled by collaboration—both within FH and with our partners. We are passionate about the impact of D2C & merchandise for artists, providing a full-service solution to grow an artist’s owned business including strategy, creative, merchandising, fulfillment, customer service, technology, and more.
The VP, Campaign Management will play a critical role at Famehouse, leading the team who acts as the nexus of all campaign activity across the business. Overseeing one of our largest teams, you will work closely with our Label partners, Account Management teams, and cross-functional partners across Famehouse and UMG to lead the exceptional execution of campaigns & client operations across our service areas—spanning merch & music campaigns across eCommerce, Tour, Retail, and Licensing.
This role is a client-facing, services operations leader, overseeing the complex project and global campaign management required to deliver against our strategy, both at scale and at the individual artist level. Candidates must be operationally savvy, possess strong communication skills and be adept at navigating dynamic artist service scenarios.
Ideal candidates have strong experience leading large teams, as well as a background in music and merchandise. Must have a passion for delivering exceptional client experiences that set the bar in super-serving both artists, labels, and most importantly, their fans.
What You’ll Do
Function & Team Leadership
- Lead the Campaign Management department, setting vision, standards, and operating models across all campaigns and channels.
- Serve as the primary point of escalation for the team, partnering closely with Account Management leadership to quickly resolve issues and unblock work.
- Build and develop a high-performing, multi-layered team; drive accountability, coaching, and clear performance expectations.
Client Service Operations Ownership
- Act as a senior, client-facing expert on campaign execution, timelines, risks, and resourcing across D2C, tour, retail and licensing.
- Navigate internal and external politics with tact while protecting realistic delivery plans and operational integrity.
- Communicate options and trade-offs clearly to artists’ teams, labels, and internal stakeholders.
Campaign & Workflow Management
- Oversee Campaign Management ownership of key milestones across the full lifecycle: planning, product and merch development, content and asset readiness, launch, and ongoing performance and inventory management.
- Ensure campaigns are executed on time, on brief, and in alignment with commercial targets and channel strategies.
- Drive rigorous documentation, status reporting, and risk management across all active campaigns.
Process Design & Optimization
- Design, refine, and scale workflows, RACIs, and playbooks for Campaign Management, grounded in your understanding of the full process map and channel-specific requirements.
- Continuously improve processes based on client feedback, team feedback, and business trends to increase speed, quality, and predictability.
- Partner with Operations, Tech, and Data teams to ensure tools, systems, and dashboards support efficient planning and execution.
Resource & Capacity Management
- Own resource allocation across the Campaign Management team in a highly dynamic, fast-paced environment.
- Balance workloads and priorities against business needs, campaign complexity, and client tiers.
- Collaborate with leadership on headcount, budget, and flexible resourcing models.
Cross-Functional Partnership
- Be an exceptional partner to leaders across Account Management, Creative, Store Management, Commercial & Merchandising, Marketing, Finance, BA, and Operations.
- Represent Campaign Management in senior forums, ensuring decisions remain executable and aligned to client expectations and service operational realities.
- Champion mutual respect for each function’s expertise and needs, and drive alignment around shared KPIs and outcomes.
What You’ll Bring
- ~10+ years of experience in campaign, production, operations, or program management in music, entertainment, merch, or consumer eCommerce.
- Deep understanding of the music and merchandise ecosystem, including labels, management, touring, retail, and licensing.
- Proven experience managing music product and/or merch across eCommerce, tour, and/or retail channels.
- Demonstrated strength in process design and optimization, turning complex workflows into clear, scalable systems.
- Track record leading large teams in a high-volume, fast-changing environment, including hiring, coaching, and organizational design.
- Strong client-facing presence and stakeholder management skills; comfortable working with senior label, artist, and internal leadership.
- Excellent judgment under pressure and a calm, solutions-oriented approach to escalations.
- Proficiency with project management and collaboration tools; confident using data to inform decisions.
- A leadership style grounded in cross-functional respect, clarity, and empowerment—not just administration.
Perks Playlist:
Join an entrepreneurial, global organization where authenticity, boldness, creativity, connection, drive, and insight aren’t just values—they’re how we work every day. Here are some of the ways we support you along the way (and just a few of the benefits we offer):
- Comprehensive medical, dental, and vision coverage
- Including 100% coverage for out-patient in-network mental health services
- Fertility coverage for eligible medical plan participants
- Wellbeing reimbursements for fitness classes, spa treatments, meal services, travel, and so much more (up to $720/year)
- Student Loan Repayment Assistance and Tuition Reimbursement
- 401(k) with 100% immediate vesting on the first 5% of your contributions, plus an additional UMG contribution
A variety of ways to prioritize much-needed time away from work including:
- Flexible Paid Time Off (PTO) for exempt employees
- 3-weeks PTO for non-exempt employees
- 2-weeks paid Winter Break
- 10 Company Holidays (including Juneteenth and Wellbeing Day)
- Summer Fridays (between Memorial Day and Labor Day)
- Generous paid parental leave for every type of parent
Check out our full overview of benefits on the
Perks Playlist page
of the career site.
Disclaimer: This job description only provides an overview of job responsibilities that are subject to change.
Universal Music Group is an Equal Opportunity Employer
We are an E-Verify employer in Alabama, Arizona, Georgia, Mississippi, North Carolina, South Carolina, Tennessee, and Utah.
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Job Category:
eCommerce
Salary Range:
$144,000 - $367,510
The actual base salary offered depends on a variety of factors, which may include, as applicable, the qualifications of the individual applicant for the position, years of relevant experience, specific and unique skills, level of education attained, certifications or other professional licenses held, and the location in which the applicant lives and/or from which they will be performing the job. All candidates are encouraged to apply.
Salary Context
This $144K-$367K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $170K across 217 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 37,339 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Universal Music Group, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $154,000 based on 8,743 positions with disclosed compensation. This role's midpoint ($255K) sits 66% above the category median. Disclosed range: $144K to $367K.
Across all AI roles, the market median is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $85,000; Mid: $147,000; Senior: $225,000; Director: $230,600; VP: $248,357.
Universal Music Group AI Hiring
Universal Music Group has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in New York, NY, US. Compensation range: $367K - $367K.
Location Context
AI roles in New York pay a median of $204,100 across 1,633 tracked positions. That's 7% above the national median.
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 37,339 open positions tracked in our dataset. By seniority: 3,672 entry-level, 23,272 mid-level, 7,048 senior, and 3,347 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (2,732 positions). The remaining 34,484 roles require on-site or hybrid attendance.
The market median for AI roles is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. Highest-paying categories: AI Engineering Manager ($293,500 median, 21 roles); AI Safety ($274,200 median, 24 roles); Research Engineer ($260,000 median, 264 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 37,339 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (33,926), AI Software Engineer (823), AI Product Manager (805). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (3,672) are outnumbered by mid-level (23,272) and senior (7,048) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 3,347 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (2,732 positions), with 34,484 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $190,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $300,688. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $145,600. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Rag (23,721 postings), Aws (12,486 postings), Rust (10,785 postings), Python (5,564 postings), Azure (3,616 postings), Gcp (3,032 postings), Prompt Engineering (2,112 postings), Kubernetes (1,713 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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