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About This Role
Rosemont, Illinois, United States (in-office Tuesday through Thursday; visa sponsorship and relocation are not available for this position)
People. Planet. Community.
Dairy’s journey starts on the farm, and the road we travel demonstrates our unwavering commitment to sustainable nutrition, as our farmers provide lasting and meaningful nourishment to people, the planet and our communities, both urban and rural.
We are a nonprofit organization located in the greater Chicagoland area and we're always looking for talented people to join our team who share the passion and motivation to promote the goodness of dairy.
Position Summary
We are seeking a dynamic and versatile Vice President to join our Marketing, Communications, and Affairs team. This role will lead and scale Dairy Management Inc.’s paid media efforts across retail media networks, e-commerce platforms, and strategic media partnerships.
This executive leader will define and implement paid B2B2C and commerce-enabled channel strategies that engage key audiences — including consumers, customers, and industry stakeholders — with dairy’s benefits, industry news, and actions. The role requires deep expertise in retail media and e-commerce campaign development, with the ability to connect media investment to sales performance, shopper behavior, and broader brand objectives.
The VP will partner with cross-functional national and local teams, including agencies, to build integrated campaigns, optimize performance, and grow impact across traditional, digital, and commerce media ecosystems.
Key Responsibilities
Strategic Leadership & Planning
- Lead the development and execution of comprehensive paid media strategies across digital, retail media networks (e.g., retailer onsite, offsite, and in-store media), e-commerce, and media partnerships in support of organizational goals.
- Ensure retail media and e-commerce strategies are fully integrated with broader marketing, communications, and brand initiatives — supporting both awareness and conversion objectives.
- Define the role of paid commerce media within the full consumer and shopper journey, from upper-funnel education to point-of-purchase activation.
- Provide day-to-day media agency oversight and collaborate closely with other MCA leaders to ensure integrated planning, alignment, and execution across channels.
Channel, Retail Media & E-commerce Campaign Management
- Oversee multi-channel paid media programs including paid search, paid social, display, programmatic, retail media networks, and e-commerce-driven placements.
- Lead strategic planning and activation across key retail and commerce partners, ensuring campaigns are optimized for shopper relevance, timing, and performance.
- Set strategic direction for channel mix, audience targeting, creative approach, messaging frameworks, and budget allocation across brand and commerce objectives.
- Optimize campaigns end-to-end — from planning and activation through measurement, sales impact analysis, and reporting.
Retail Media, Sales Data & Performance Analytics
- Establish KPIs and measurement frameworks that connect paid media performance to commerce outcomes, including sales lift, conversion, ROAS, and retailer-specific metrics.
- Analyze and interpret retail sales, shopper, and e-commerce data to inform optimization, future investment decisions, and strategic recommendations.
- Translate complex performance and sales data into clear insights and narratives for senior leadership and cross-functional partners.
- Leverage retailer and platform data to refine audience strategies, test new approaches, and scale successful tactics.
Media Partnerships & Vendor Relations
- Develop and maintain strong relationships with media partners, publishers, retail media networks, and platform representatives.
- Evaluate, negotiate, and structure media and retail partnerships that deliver incremental value, innovation, and measurable business impact.
- Stay current on evolving retail media capabilities and emerging commerce platforms to ensure DMI remains competitive and forward-looking.
Cross-Functional Collaboration
- Collaborate closely with creative, content, insights, and communications teams to ensure paid media — including retail and e-commerce — is fully integrated with messaging and storytelling.
- Engage with and support regional (State & Region) business development and marketing teams on local retail efforts for national/local collaboration on multi-channel paid media programs, including management of backend technology platform.
- Partner with e-commerce, Strategic Intelligence, retail and partnership teams to align media strategy with sales priorities, retailer partner needs, and performance insights.
- Serve as a strategic advisor to senior leadership on paid media, retail media, and e-commerce trends, opportunities, and risks.
Thought Leadership
- Stay abreast of industry trends, emerging retail media models, commerce innovation, and new technologies — including AI, automation, and advanced measurement — to elevate DMI’s paid media capabilities.
New Hire Salary Range - $140,000-$185,000 annually. This is a salary range that DMI believes, at the time of this posting, that it might be willing to pay for the posted job in the location specified.
Requirements
Education & Experience
- Bachelor’s degree in marketing, communications, business, or a related field.
- 10+ years of progressively responsible experience in paid media, performance marketing, or digital marketing leadership roles.
- Demonstrated senior-level experience leading retail media and e-commerce campaigns, ideally across multiple retailer platforms, and integrating them into broader brand and communications strategies.
- Proven ability to analyze and interpret sales, shopper, and e-commerce performance data to drive optimization and strategic decisions.
- Track record managing media budgets and delivering measurable ROI across both brand and commerce objectives.
Skills & Competencies
- Deep understanding of digital marketing, retail media ecosystems, e-commerce platforms, and performance measurement frameworks.
- Strong analytical capabilities with the ability to connect media investment to sales and business outcomes.
- Strategic thinker who can balance long-term brand building with near-term commerce performance.
- Strong negotiation skills and experience managing agency and media partner relationships.
- Exceptional leadership, communication, and cross-functional collaboration skills.
- Foster a culture of innovation, accountability, data-driven decision-making, and continuous learning.
- Provide coaching, performance management, and development planning for direct reports.
Preferred Attributes
- Experience in CPG, food & beverage, retail, or agency environments with a strong commerce orientation.
- Familiarity with complex, multi-stakeholder or industry-led marketing organizations.
- Experience driving media innovation and scaling new retail media or commerce capabilities
Benefits
We know that in order to meet our goal of growing dairy demand, we need the best people. We offer competitive compensation and generous benefits to help our employees balance their work and personal lives. Our office is conveniently located, taking less than 10 minutes to walk from CTA's Blue Line Rosemont station. We offer regular and chocolate milk on tap.
Our comprehensive health and welfare plans offer medical, dental, vision, paid parental leave, life, short-term and long-term disability and flexible spending accounts (health care, dependent care, transit and parking). Our 401k provides up to a 10% match and includes a Roth account. DMI reserves the right to change or end its benefits plans or programs at any time.
Dairy Management Inc.™ is proud to be an Equal Employment Opportunity Employer committed to the principles of diversity. Qualified applicants will receive consideration for employment without regard to race, color, religion, ethnicity, sex, disability, age, sexual orientation, gender identity, protected veteran status, or any other characteristic protected by applicable law.
ABOUT DAIRY MANAGEMENT INC.
Dairy Management Inc.™ (DMI) is funded by America’s nearly 28,000 dairy farmers, as well as dairy importers. Created to help increase sales and demand for dairy products, DMI and its related organizations work to increase demand for dairy through research, education and innovation, and to maintain confidence in dairy foods, farms and businesses. DMI manages National Dairy Council and the American Dairy Association, and founded the U.S. Dairy Export Council and the Innovation Center for U.S. Dairy. DMI works with state and regional promotion organizations to implement these programs across the country.
We regret it is not possible to communicate with candidates except those who most closely match our requirements. Thank you.
Salary Context
This $140K-$185K range is below the median 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 Dairy Management Inc., 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 ($162K) sits 6% above the category median. Disclosed range: $140K to $185K.
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.
Dairy Management Inc. AI Hiring
Dairy Management Inc. has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Rosemont, IL, US. Compensation range: $185K - $185K.
Location Context
Across all AI roles, 7% (2,732 positions) offer remote work, while 34,484 require on-site attendance. Top AI hiring metros: New York (1,633 roles, $204,100 median); Los Angeles (1,356 roles, $179,440 median); San Francisco (1,230 roles, $240,000 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 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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