Interested in this AI/ML Engineer role at The Estée Lauder Companies?
Apply Now →About This Role
The Estée Lauder Companies Inc. is one of the world’s leading manufacturers, marketers, and sellers of quality skin care, makeup, fragrance, and hair care products, and is a steward of luxury and prestige brands globally. The company’s products are sold in approximately 150 countries and territories under brand names including: Estée Lauder, Aramis, Clinique, Lab Series, Origins, M·A·C, La Mer, Bobbi Brown Cosmetics, Aveda, Jo Malone London, Bumble and bumble, Darphin Paris, TOM FORD, Smashbox, AERIN Beauty, Le Labo, Editions de Parfums Frédéric Malle, GLAMGLOW, KILIAN PARIS, Too Faced, Dr.Jart\+, the DECIEM family of brands, including The Ordinary and NIOD, and BALMAIN Beauty.
Description
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By deeply understanding consumer needs and trends, uncovering business value, and working with brand, supply chain, data, and technology teams, you can be at the forefront of innovation in one of the most exciting verticals in eCommerce and Omnichannel. The Global Omnichannel Team delivers best⁃in⁃class consumer experiences globally for Estée Lauder Companies brands. The Estée Lauder Companies Global Omnichannel team is looking for an exceptional candidate who will help shape, evolve and maximize Ship from Store and related initiatives ⁃ innovating and scaling our capabilities globally.
This role maintains and communicates the product vision, strategy and roadmap for their product area(s). They are responsible for discovering, delivering and optimizing Omnichannel products and capabilities that fundamentally transform how our consumers can find, purchase and enjoy beauty products across our global portfolio of brands. This is a key role that works collaboratively with brands, business partners, solution architects, data, and delivery teams spanning Online, Stores, Supply Chain, Retail Operations and more. You'll help shape our culture and our people and be an ambassador for Global Omnichannel across the ELC Global organization. Global Omnichannel is a fast⁃growing team and this role has significant growth opportunity.
Primary Responsibilities:
- Establish vision, strategy, and execution of Omnichannel products including Ship From Store and Click and Collect, through understanding of strategic brand direction, technology architecture, big picture consumer needs, and business opportunities (e.g. inventory efficiency, fulfillment cost optimization)
- Own end⁃to⁃end implementationand strategy for ELC Ship from Store capability, including development of order routing logic, business rules, use case development and prioritization, management of operational workstreams and in⁃store processes, and ownership of KPIs and insights in partnership with cross⁃functional teams and Brands
- Rigorously and systematically use data and analytics to define product, uncover opportunities, track performance, and drive decision making
- Ideate, build and implement innovative and best⁃in⁃class Omnichannel products and experiences that deliver business value and improved consumer experiences
- Create and communicate product strategy across organizations and teams to influence stakeholders to align behind the objectives
- Promote inclusive and innovative culture and principles within cross functional teams, while setting new standards in executional and operational excellence
- Track and set OKRs to measure success/failure for the Omnichannel products and capabilities you manage
- Inspire, enable and empower cross functional teams to execute with urgency and deliver incremental consumer and business value
- Proactively influence cross⁃department agendas to deliver human centered outcomes that balance short and long term objectives
- Use strategic and tactical thinking to identify and prioritize opportunities in highly ambiguous contexts, organize work in deep detail to align long term vision with iterative execution
Qualifications
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- BA/BS in related field or relevant experience, MBA a plus
- 6\+ years work experience in management consulting, product management, ecommerce operations, or similar
- Experience with supply chain/logistics in eCommerce or consumer products a plus
People who are successful in this role demonstrate:
- Strong project management skills and "owner" mentality, ability to marshal resources and key stakeholders and drive a project through to completion despite setbacks
- Strong problem⁃solving skills, outstanding quantitative and analytical skills, including P\&L development and understanding of key drivers that drive profitability in a multi⁃channel retailer
- Ability to prioritize effectively
- Excellent communicator with ability to build strong cross⁃functional relationships, to understand incentives, and to ensure alignment in a matrixed organization
- Executive presence with high business IQ
- Ability to work on several projects simultaneously and to thrive in a project⁃based, matrixed environment with a closely intertwined team
- Strong attention to detail and results orientation, high work ethic and persistence to drive an initiative to completion, a "roll up the sleeves" attitude towards tackling a challenge
Pay Range:
Anticipated Base Salary Range $102,000\.00 to $167,550\.00 (Depending on qualifications, skills, experience and/or budget), based on a 40 hour work week (range to be scaled accordingly). In addition, The Estée Lauder Companies offers a variety of benefits to eligible employees, including health insurance coverage (medical, dental, and vision insurance), wellness and family support programs, life and disability insurance, retirement savings plans, education\-related programs, paid holidays and vacation time. In addition, the Company maintains highly competitive incentive compensation programs (role eligibility may vary based on terms of the respective plan(s)).
You may be eligible to participate in the applicable Commission/Bonus Plan, under the plan guidelines in effect at the time of hire. Additional details regarding the commission plan will be provided as part of your onboarding.
Equal Opportunity Employer
We are an equal\-opportunity employer. Minorities, women, veterans, and individuals with disabilities are encouraged to apply. Accommodations for job applicants with disabilities are available on request.
Artificial Intelligence is used to compare and screen an applicant’s resume as against the posted job description.
Salary Context
This $102K-$167K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $180K across 1841 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 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At The Estée Lauder Companies, 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 $218,750 based on 3,817 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($134K) sits 38% below the category median. Disclosed range: $102K to $167K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
The Estée Lauder Companies AI Hiring
The Estée Lauder Companies has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in New York, NY, US. Compensation range: $167K - $167K.
Location Context
AI roles in New York pay a median of $220,000 across 1,045 tracked positions.
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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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