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About This Role
AI & AGENT PRODUCT MANAGER, RDQR DIGITAL TRANSFORMATION
HUNT VALLEY, MD, US, 21031 McCormick & Company, Inc., a global leader in the spice, flavor, and seasonings industry, is seeking an AI & Agent Product Manager, RDQR Digital Transformation. This new hire will work at the Technical Innovation Center located in Hunt Valley, MD.
McCormick & Company, Incorporated is a global leader in flavor with approximately 14,000 employees worldwide. With over $6 billion in annual sales across 160 countries and territories, we manufacture, market, and distribute spices, seasoning mixes, condiments, and other flavorful products to the entire food industry including e-commerce, retail,food manufacturers and foodservice businesses. Our most popular brands include McCormick, French's, Frank's RedHot, Stubb's, OLD BAY, Lawry's, Zatarain's, Ducros, Vahiné, Cholula, Schwartz, Kamis, DaQiao, Club House, Aeroplane, and Gourmet Garden. Every day, no matter where or what you eat or drink, you can enjoy food flavored by McCormick.
As a company recognized for its exceptional commitment to employees, McCormick offers a wide variety of benefits, programs, and services. Benefits include, but are not limited to, tuition assistance, medical, dental, vision, disability, group life insurance, 401(k), profit sharing, paid holidays, and vacations.
Position Summary: McCormick is seeking an AI and Agent Product Manager to support digital transformation initiatives within the R&D, Quality and Regulatory function working out of our Technical Innovation Center. In this role, you will help translate business needs into requirements and delivery inputs for analytics, automation, data science, AI-enabled, and digital workflow solutions. You will work with business stakeholders, product leads, data scientists, data engineers, and technology partners to support assigned products and workstreams from discovery through testing, adoption, and value tracking.
Why McCormick?
- Help shape AI-enabled innovation at a global flavor leader
- Shape practical AI-enabled business solutions
- Collaborate across business and technology
- Build experience across RDQR functions
- Support products from discovery to adoption
- Grow product, analytics, and AI skills
Position Overview The AI and Agent Product Manager supports defined RDQR digital products and workstreams. This individual contributes to discovery, requirements, roadmap materials, prioritization inputs, business cases, testing, adoption, and value tracking. The role partners closely with RDQR stakeholders and technical delivery teams. Material prioritization decisions, scope trade-offs, and stage-gate approvals are escalated to the appropriate Director or Product Lead.
Key Responsibilities
- Support assigned AI and digital workstreams
- Gather and document business and technical requirements
- Prepare roadmap and prioritization materials
- Support business-case and value-tracking activities
- Develop user stories and acceptance criteria
- Coordinate testing, feedback, and adoption activities
- Prepare project updates and stage-gate materials
- Partner with business and technical teams
Required Qualifications
- Bachelor’s degree in Business, Analytics, Data Science, Computer Science, Engineering, Food Science, or related field
- Approximately 4 to 6 years of experience in analytics, automation, digital transformation, product management, business analysis, or related work
- Experience supporting digital, analytics, automation, or AI-enabled products or workstreams
- Experience gathering business requirements and developing user stories, acceptance criteria, or delivery documentation
- Experience supporting testing, adoption, stakeholder communications, or value-tracking activities
- Strong communication, organization, facilitation, and problem-solving skills
- Ability to collaborate effectively across business and technical teams
- Familiarity with analytics, automation, data, or AI technologies
Preferred Qualifications
- Master’s degree in a technical, scientific, quantitative, or business discipline
- Scrum, Agile, product management, or PMP certification
- Experience in R&D, Quality, Regulatory, product development, consumer science, manufacturing, or consumer packaged goods
- Familiarity with Power BI, Power Automate, UiPath, Power Apps, Azure, Python, SQL, or related tools
- Exposure to machine learning, GenAI, agentic AI, predictive analytics, or workflow automation
- Experience working with global or offshore delivery teams
- Familiarity with data governance, data products, or digital-product delivery practices
#LI-CG1
As a general policy, McCormick does not offer employment visa sponsorships upon hire or in the future.
McCormick & Company is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected veteran status, age, or any other characteristic protected by law.
Base Salary: $80,500 - $137,000
Base salary compensation will be determined based on factors such as geographic location, skills, education, experience for this role, and/or internal equity of our current employees as part of any final offer. This position is also eligible to participate in McCormick’s Incentive Bonus (MIB) Plan. In addition to a competitive compensation package, permanent employees of McCormick are eligible for our extensive Total Rewards programs that include:
- Comprehensive health plans covering medical, vision, dental, life and disability benefits
- Family-friendly benefits such as paid parental leave, fertility benefits, Employee Assistance Program, and caregiver support
- Retirement and investment programs including 401(k) and profit-sharing plans
WHY WORK AT MCCORMICK?
As a McCormick employee you’ll be empowered to focus on more than your individual responsibilities. You’ll have the opportunity to be part of something bigger than yourself—to have a say in where the company is going and how it’s growing.
Between our passion for flavor, our 130-year history of leadership and integrity, the competitive and comprehensive benefits we offer, and our culture, which is built on respect and opportunities for growth, there are many reasons to join us at McCormick.
Nearest Major Market: Baltimore
Salary Context
This $80K-$137K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $178K across 2239 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 11,520 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At McCormick & Company, 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 $212,040 based on 13,780 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($108K) sits 49% below the category median. Disclosed range: $80K to $137K.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,250; VP: $235,830.
McCormick & Company AI Hiring
McCormick & Company has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Hunt Valley, MD, US. Compensation range: $137K - $137K.
Location Context
Across all AI roles, 6% (708 positions) offer remote work, while 10,737 require on-site attendance. Top AI hiring metros: New York (3,257 roles, $221,000 median); San Francisco (2,766 roles, $260,550 median); Los Angeles (1,580 roles, $210,000 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 11,520 open positions tracked in our dataset. By seniority: 140 entry-level, 5,630 mid-level, 4,176 senior, and 1,574 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (708 positions). The remaining 10,737 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 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 11,520 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,769), AI Software Engineer (586), AI Product Manager (511). 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 (140) are outnumbered by mid-level (5,630) and senior (4,176) 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 1,574 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (708 positions), with 10,737 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 $213,480. Top-quartile roles start at $264,000, and the 90th percentile reaches $318,400. 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 Safety roles lead at $266,050 median, while Prompt Engineer roles sit at $140,000. 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: Python (2,267 postings), Aws (1,178 postings), Azure (972 postings), Rag (924 postings), Gcp (715 postings), Pytorch (586 postings), Claude (572 postings), Kubernetes (559 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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