Interested in this AI/ML Engineer role at European Wax Center?
Apply Now →Skills & Technologies
About This Role
At European Wax Center, our mission is simple: help everyone who walks through our doors feel comfortable, confident, and radiant in their own skin. We believe that when you feel bold, you’re unstoppable, and that’s exactly what we want you to bring!
If you’re a proactive leader who’s passionate about people, eager to exceed goals, and ready to thrive in a dynamic, fast\-growing organization, we’d love to meet you. Step into our lively Center Manager role and help us keep driving that sense of empowerment for guests and team members alike.
Why You’ll Love It Here
Competitive Pay \& Performance Bonuses
- We start our Center Manager at a competitive salary, plus commission opportunities and monthly performance bonuses. We believe in rewarding your drive and determination. If you excel, your earning potential follows.
Benefits Package
- In addition to a competitive wage, we offer medical, dental, and vision insurance, a 401(k), and paid time off so you can truly recharge. We want you to feel your best, both on and off the job.
Supportive Culture
- We take pride in our upbeat, close\-knit environment where teamwork is how we succeed. Expect leadership that values your input, celebrates milestones, and encourages every team member to shine.
Your Day\-to\-Day Impact
Inspire \& Lead
- Recruit, train, and develop an enthusiastic team of associates and wax specialists.
- Provide consistent feedback and coaching to elevate performance and ensure everyone feels supported, challenged, and recognized.
Drive Sales \& Profitability
- Set clear sales targets and motivate your team to reach or surpass these goals.
- Partner with our District Manager to analyze metrics, adjust strategies, and seize every revenue opportunity.
Deliver Exceptional Guest Experiences
- Uphold European Wax Center’s unwavering commitment to cleanliness, professionalism, and personalized service.
- Foster a welcoming atmosphere that makes guests feel at home and excited to return.
Champion Local Community Engagement
- Build relationships with local residents, visitors, and neighboring businesses.
- Represent EWC in community events or partnerships that reinforce our goal of bringing confidence and radiance to as many people as possible.
Operational Excellence
- Oversee daily center operations, from inventory and scheduling to budgeting and payroll.
- Safeguard compliance with brand standards. Our reputation as the \#1 wax center depends on your attention to detail.
Cultivate a Positive, Productive Environment
- Celebrate personal and team milestones.
- Encourage open communication, problem\-solving, and continuous learning so each associate can reach new heights in their career.
Who We’re Looking For
Leadership Experience (2\+ Years)
- You’ve managed a team in retail, hospitality, beauty, or a service\-oriented field, guiding at least 5 direct reports to outstanding results.
Track Record of Over\-Delivering
- Whether it’s consistently beating sales quotas or building high\-performing teams, we want someone relentlessly focused on achieving and exceeding goals.
Excellent People Skills
- You know how to energize employees, maintain morale, and treat guests with warmth. Strong conflict\-resolution skills are a must. You thrive under pressure and keep calm even when challenges arise.
Entrepreneurial Mindset
- We’re looking for a go\-getter who loves analyzing data, brainstorming new strategies, and turning ideas into results. A strong sense of ownership is key. You will be a driving force behind your center’s success.
Passion for Beauty \& Confidence
- You embrace the power of feeling great about yourself and enjoy sharing that energy with others. Familiarity with waxing or beauty services is a plus, but a desire to learn and advocate for our guests is what truly matters.
Flexible \& Reliable
- Our center is open 7 days a week. You’ll coordinate schedules in a way that meets guest needs while still protecting your own work\-life balance. Weekends, evenings, and some holidays may be part of the job.
Ready to Join Our Confidence Revolution?
If you’re fired up about leading a team that makes people look and feel incredible, this is your chance to shine. With our strong brand reputation, supportive culture, and dynamic growth trajectory, our Patel\-owned franchise is the ideal place to take your leadership career to the next level.
Apply Now and let’s reveal the best in each other, one wax at a time.
*Each European Wax Center® location is independently owned and operated by a franchisee. The franchisee is the sole employer for all employment\-related matters and solely responsible for all decisions affecting employees.*
European Wax Center began as a family\-owned business. Since 2004, we've provided our guests with a first\-class waxing experience centering around:
- Our proprietary Comfort Wax®
- Private waxing suites
- A crisp, clean environment
- And the most professionally trained estheticians in the industry
From day one, we've been putting our values into action to delight our guests with an exceptional waxing experience.
Pay:
- Commission pay
- Bonus pay
Benefits:
- Paid time off
- Health insurance
- Dental insurance
- Vision insurance
- 401(k)
- Employee discount
Job Type: fulltime, parttime
Education: No education required
Work location: On\-site
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 European Wax Center, 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.
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.
European Wax Center AI Hiring
European Wax Center has 6 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Sioux Falls, SD, US, Edgewater, NJ, US, Closter, NJ, US. Compensation range: $41K - $62K.
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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.