Interested in this AI/ML Engineer role at Michael Kors?
Apply Now →About This Role
Michael Kors is always interested in hearing from talented, globally-minded individuals with a passion for fashion.
If you enjoy working in a creative, fast-paced environment, then we would love to hear from you!
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Who You Are
The Lead Retoucher & AI Imaging Specialist is a hands-on creative technologist responsible for elevating ecommerce imagery through expert retouching, AI-assisted workflows, and quality leadership. Reporting to the Associate Director, Digital Imaging & Content Supply Operations, this role sits at the intersection of craftsmanship and innovation—driving excellence in traditional retouching while helping shape how AI-generated imagery is responsibly introduced into production.
This is a highly collaborative, execution-focused role for someone who loves building scalable workflows, refining imagery at a premium level, and staying at the forefront of imaging technology.
What You’ll Do
Lead Retouching & Quality Execution
- Act as the lead retoucher for ecommerce photography across still-life and on-figure imagery
- Guide and support a team of two ecommerce retouchers through complex edits, edge cases, and tight production timelines
- Step in hands-on when higher-level expertise or additional capacity is required
- Ensure consistent color accuracy and product integrity across all imagery
- Perform targeted quality reviews to maintain brand standards at scale
AI Imaging & Innovation
- Create, test, and refine prompts for AI-generated and AI-assisted imagery
- Evaluate AI outputs for realism, brand alignment, and production readiness
- Stay current on emerging AI imaging tools and apply them thoughtfully to production use cases
- Help determine which content types are best suited for AI generation versus traditional photography
Vendor & Workflow Collaboration
- Partner with the Associate Director to evaluate, onboard, and support offshore retouching partners
- Review offshore output, provide clear feedback, and guide corrective action when needed
- Collaborate with photographers, art directors and content operations partners
- Contribute to scalable workflows that balance automation, offshore production, and internal editing
Document best practices as tools, standards, and workflows continue to evolve *
You’ll Need to Have
- Bachelor’s degree in photography, digital media, visual arts, or a related field
- 6+ years of professional retouching experience in ecommerce or high-volume commercial environments
- Advanced expertise in Adobe Photoshop and modern retouching workflows
- Hands-on experience with AI-generated or AI-assisted imaging, including prompt development
- Experience with DAM tools such as Bynder or similar
- Experience reviewing and coordinating work with offshore or external partners
- Strong communication skills and a collaborative mindset
- High attention to detail and comfort working in fast-paced, deadline-driven environments
Fashion or luxury retail experience preferred *
MK Perks:
- Generous Paid Time Off & Holiday Calendar
- Summer Fridays
- Internal Mobility Across Brands
- Cross-brand Discount
- Exclusive Employee Sales
- Fav 5 Cards (MK Discount for friends and family)
- 401k Match
- Paid Parental Leave
- Thrive Wellness Program
- Commuter Benefits
Gym Discounts *
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The Company is an equal employment opportunity employer. The Company’s policy is not to unlawfully discriminate against any applicant or employee on the basis of race, color, sex, sexual orientation, gender identity, religion, national origin, age, military status, disability, genetic information or any other consideration made unlawful by applicable federal, state, or local laws. The Company also prohibits harassment of applicants and employees based on any of these protected categories.
At Capri Holdings Limited, we are committed to providing a fair and accessible recruitment process. If you require a reasonable accommodation for the interview or application process, please contact our Talent Acquisition team at [email protected].
In compliance with certain Pay Transparency laws, employers are required to disclose a compensation range. The range for this position will vary based on role requirements, skill set, and years of experience. Please note that for salaried roles, the figures reflect full-time equivalency, while for hourly roles, the figures represent the applicable hourly rate.
Compensation Range:
100,000.00 - 120,000.00 USD
Salary Context
This $100K-$120K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $175K across 1356 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 8,943 AI roles we're tracking, AI/ML Engineer positions make up 75% of the market. At Michael Kors, 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 in Demand for This Role
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 $212,000 based on 11,866 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $228,700. This role's midpoint ($110K) sits 48% below the category median. Disclosed range: $100K to $120K.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,250; VP: $235,000.
Michael Kors AI Hiring
Michael Kors has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in New York, NY, US. Compensation range: $120K - $120K.
Location Context
AI roles in New York pay a median of $221,000 across 2,878 tracked positions. That's 4% 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 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). 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 (175) are outnumbered by mid-level (4,132) and senior (3,268) 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 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 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 $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. 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 $253,100 median, while Prompt Engineer roles sit at $141,440. 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 (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 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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