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About This Role
About IMG Academy
IMG Academy is the world’s leading sports education brand, providing a holistic education model that empowers student\-athletes to win their future while preparing them for college and for life. IMG Academy has been nationally recognized by organizations including Sports Business Journal, USA Today, and the Best and Brightest Companies to Work For for its workplace culture, innovation, and commitment to developing people both on and off the field.
IMG Academy provides growth opportunities for student\-athletes and partners through an innovative suite of on\-campus and online experiences:
- Boarding school and camps, delivered on a state\-of\-the\-art campus in Bradenton, Florida
- Online coaching through IMG Academy\+, focused on personal development through the lens of sport and performance
- Online college recruiting through NCSA College Recruiting and SportsRecruits, providing industry\-leading recruiting education, tools, and access to a network of more than 40,000 college coaches for student\-athletes, families, club coaches, and event operators
- Elevate by IMG Academy, a performance and personal development solution that delivers mindset, leadership, and wellbeing programming to schools, colleges, and organizations through a combination of digital content and immersive experiences
Position Summary:
IMG Academy is seeking a strategic Director of Paid Media \& Performance Marketing to lead customer acquisition across its global sports education portfolio, including camps, boarding school, digital products and NCSA college recruiting services. This leader will own the strategy, execution, and optimization of paid digital acquisition channels, driving growth in qualified leads, enrollments, and revenue. The role manages a significant media investment and scales high\-impact, data\-driven programs across search, social, video, programmatic, and emerging platforms.
The Director will lead full\-funnel paid media initiatives that drive customer acquisition, increase brand awareness, and accelerate revenue growth. This role partners closely with product, brand, website, data and analytics teams while managing agency relationships to ensure campaigns deliver measurable business impact. The ideal candidate brings deep performance marketing expertise, strong analytical capabilities, and a proven ability to scale high\-performing digital campaigns.
Position Responsibilities:
Strategic Leadership \& Planning
- Develop and lead the paid media and performance marketing strategy for IMG Academy aligning acquisition initiatives with enrollment, revenue, and growth objectives across campus programs, digital products and recruiting services.
- Identify scalable customer acquisition opportunities across global markets while establishing performance goals, acquisition targets, and channel strategies that drive efficient growth.
- Build and manage annual and monthly paid media roadmaps, budgets, and forecasts, ensuring media investments maximize return and support business priorities.
- Lead agency relationships and cross\-functional collaboration with product, brand, and web teams to execute integrated paid media strategies across search, social, programmatic, affiliate, and emerging channels.
- Provide thought leadership on paid media strategy staying ahead of platform and industry trends, and fostering a culture of experimentation and continuous performance improvement.
Campaign Management \& Optimization
- Oversee the execution and performance of paid media campaigns, ensuring delivery against timelines, budgets, and defined performance goals.
- Guide agency partners on performance improvements through structured testing and optimization across creative, landing pages, bidding strategies, audience targeting, and channel mix.
- Implement and refine audience segmentation and lifecycle targeting strategies to deliver the right message to the right audience at each stage of the funnel.
- Establish and drive a rigorous testing framework including A/B testing, creative experimentation, and audience expansion to continuously improve campaign performance.
- Partner closely with web and product teams to optimize landing pages and digital experiences, improving conversion rates, supporting ecommerce initiatives, and ensuring paid traffic is directed to high\-performing, conversion\-focused destinations.
- Leverage AI\-driven tools and automation to optimize creative, targeting, and bidding strategies, improving efficiency and scaling performance across paid channels.
- Apply advanced measurement frameworks, including Marketing Mix Modeling (MMM) and Multi\-Touch Attribution (MTA), to inform media investment decisions and optimize channel effectiveness
Budget Management \& Performance Analytics
- Own and manage the paid media budget, ensuring efficient allocation of spend across channels to maximize ROI and support business priorities.
- Analyze campaign performance and provide regular reporting, insights, and strategic recommendations to senior leadership, leveraging AI\-driven analytics and automation to identify optimization opportunities.
- Establish KPIs, attribution frameworks, and measurement strategies, including Marketing Mix Modeling (MMM) and Multi\-Touch Attribution (MTA), to evaluate channel effectiveness and guide future investment decisions.
- Allocate and manage test\-and\-learn budgets to evaluate emerging platforms, new audience segments, and incremental growth channels, using data\-driven experimentation to accelerate scalable results.
- Integrate AI tools and automation to streamline reporting, optimize budget allocation, and improve forecasting accuracy across campaigns
Cross\-Functional Collaboration
- Partner with Product, Brand, and Creative teams to develop high\-impact ad creatives that align with business objectives and brand standards.
- Collaborate closely with Web, Ecommerce, and Digital Product teams to optimize landing pages, user experiences, and conversion paths, ensuring paid traffic drives maximum engagement and revenue.
- Work with Data \& Analytics teams to evaluate campaign performance, uncover actionable insights, and refine media strategies, including identifying growth opportunities across products, sports, and geographies.
- Align with Product and Sales teams to ensure paid media initiatives support broader business, revenue, and customer acquisition goals.
Knowledge, Skills and Abilities:
- Bachelor’s degree in Marketing, Business, Advertising or a related field; MBA or advanced degree preferred.
- 8\+ years of experience in paid media with at least 3 years in a leadership or management role, ideally with paid media agency experience.
- Collaborative leader with a mentorship mindset, fostering a team\-first culture focused on shared success and collective impact
- Proven track record of scaling high\-performing paid media campaigns across multiple channels.
- Deep expertise in platforms such as Google Ads, Meta Ads Manager, and other major digital advertising ecosystems.
- Strong understanding of digital marketing analytics, attribution models (MMM \& MTA), and campaign optimization techniques.
- Experience with tools such as Google Analytics, Tableau, and Google Looker Studio.
- Familiarity with CRM and marketing automation platforms (Salesforce Marketing Cloud) and e\-commerce is preferred.
- Strong leadership, communication, and stakeholder management skills with the ability to present insights and recommendations to senior executives.
- Ability to manage multiple priorities in a fast\-paced, performance\-driven environment.
Background Requirements:
- Requires a background check upon offer
- Requires a drug test upon offer
Benefits:
As a full\-time member of our team, you will enjoy a comprehensive offering listed below. Connect with your talent acquisition specialist to learn more about benefits for our part\-time and seasonal/temporary roles.
- Comprehensive Medical, Dental and Vision
- Flexible Spending Account and Health Savings Account options
- 401k with an Employer Match
- Short Term and Long Term Disability
- Group and Supplemental Life \& AD\&D
- Gym Discount Program
- Pet Insurance
- Wellbeing Program
- and more!
Don’t meet every single requirement? We are dedicated to building a diverse, inclusive, authentic workplace, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles.
Get to know us better:
www.imgacademy.com
www.imgacademy.com/careers
IMG Academy provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
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 26,159 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At IMG Academy, 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 $166,983 based on 13,781 positions with disclosed compensation. Director-level AI roles across all categories have a median of $244,288.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
IMG Academy AI Hiring
IMG Academy has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Bradenton, FL, US.
Location Context
Across all AI roles, 7% (1,863 positions) offer remote work, while 24,200 require on-site attendance. Top AI hiring metros: Los Angeles (1,695 roles, $178,000 median); New York (1,670 roles, $200,000 median); San Francisco (1,059 roles, $244,000 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 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 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 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). 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 (2,416) are outnumbered by mid-level (16,247) and senior (5,153) 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 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 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 $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. 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 $122,200. 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 (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 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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