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About This Role
Requisition Number: 222675
Job Description
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Cintas is seeking a Sales Representative to focus on new business\-to\-business account development in our First Aid and Safety Division. Responsibilities include prospecting, cold calling, setting appointments with prospects, presenting programs and meeting a sales quota. Sales Representatives will also transport samples of products for presentations. Cintas provides a thorough sales training program, including product knowledge, mentorship, sales process and business development strategies.
Key Responsibilities:
- Generating revenue and meeting sales targets
- Developing and qualifying leads within respective territory to drive additional sales opportunities through cold\-calling and lead generation campaigns
- Gathering and utilizing business intelligence on prospects to support sales calls, product presentations and driving new business
Our Sales Representatives enjoy:
- Solid base salary and commission potential
- Extensive car package (lease/gas/insurance/maintenance allowance)
- Monthly/Quarterly performance bonuses \& incentives
- Comprehensive 12\-week sales training program
- Mentorship program
- Tablet \& AirCard
- Annual recognition events
Skills/Qualifications
-------------------------
Required
- Minimum 1 year outside sales experience or successful completion of a Cintas sales training program
- Valid driver's license
- High School Diploma/GED; Bachelor's Degree preferred
Preferred
- New business\-to\-business (B2B) sales experience
- Hunter sales mentality \- goal driven and self\-motivated
- Proficiency with Microsoft Office (Word, Excel, PowerPoint, Outlook), Intranet/Internet and Contact Management System
Benefits
Cintas offers comprehensive and competitive medical, dental and vision benefits, with premiums below the national average. We offer flexibility with four different medical plan options; one plan is offered at zero cost.
Additionally, our employee\-partners enjoy:
- Competitive Pay
- 401(k) with Company Match/Profit Sharing/Employee Stock Ownership Plan (ESOP)
- Disability, Life and AD\&D Insurance, 100% Company Paid
- Paid Time Off and Holidays
- Skills Development, Training and Career Advancement Opportunities
Compensation
A reasonable estimate of total compensation for this role ranges between $60,000 \- $150,000/Year and is a combination of base salary plus earned commissions. The range takes into account factors that are considered in making compensation decisions including, but not limited to, skill sets, experience and training, performance, and other business and organization needs. This disclosed range has not been adjusted for applicable geographic differentials associated with the location at which the position may be filled. Please note, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decision are dependent on the facts and circumstances of each decision. Company Information
Cintas Corporation helps more than one million businesses of all types and sizes get Ready™ to open their doors with confidence every day by providing products and services that help keep their customers’ facilities and employees clean, safe, and looking their best. With offerings including uniforms, mats, mops, towels, restroom supplies, workplace water services, first aid and safety products, eye\-wash stations, safety training, fire extinguishers, sprinkler systems and alarm service, Cintas helps customers get Ready for the Workday®. Headquartered in the U.S., Cincinnati, OH, Cintas is a publicly held Fortune 500 company traded over the Nasdaq Global Select Market under the symbol CTAS and is a component of both the Standard \& Poor’s 500 Index and Nasdaq\-100 Index.
Cintas Corporation is proud to be an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy), national origin, age, genetic information, disability, protected veteran status, or any other characteristic or category protected by local, state, or federal law.
This job posting will remain open for at least five (5\) days.
Job Category: Sales
Organization: First Aid and Safety
Employee Status: Regular
Schedule: Full Time
Shift: 1st Shift
Salary Context
This $60K-$150K range is above the median for AI/ML Engineer roles in our dataset (median: $100K across 15465 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 26,159 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Cintas, 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. Mid-level AI roles across all categories have a median of $131,300. This role's midpoint ($105K) sits 37% below the category median. Disclosed range: $60K to $150K.
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.
Cintas AI Hiring
Cintas has 18 open AI roles right now. They're hiring across AI/ML Engineer, AI Product Manager. Positions span Omaha, NE, US, Houston, TX, US, Ridgeland, MS, US. Compensation range: $150K - $150K.
Location Context
AI roles in Seattle pay a median of $223,600 across 678 tracked positions. That's 22% 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 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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