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Staff Machine Learning Engineer

Pay
$119,300–196,600/year · BaseAnnual period assumed. Location-specific pay — pay source
Pay Range: The anticipated base salary range for this position is $119,300.00 to $196,600.00. Exact salary depends on several factors such as experience, skills, education, and budget. Salary range may vary based on geographic location. In addition to base salary, this position is eligible for participation in a highly competitive bonus program as well as participation in the share incentive plan. In addition, In addition to base salary, this position is eligible for participation in a highly competitive bonus program with the possibility for overachievement based on performance and company results. 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, paid leave programs, education-related programs, paid holidays and vacation time, and many others. Many of these benefits are subsidized or fully paid for by the company.
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Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting

What you’ll work on

Full posting
  • Design, build, test, and deploy production agentic and LLM-powered products on Google Cloud

  • Build the shared platform, tooling, and harnesses beneath those products

  • Bring software-engineering rigor to stateful and transactional (OLTP) services

  • Author design documents and review others' designs and deliverables

  • Mentor and grow engineers and scientists

From the employer’s posting
Design, build, test, and deploy production agentic / LLM-powered products end-to-end on Google Cloud
along with the shared platform, tooling, and harnesses beneath them
Bring strong software-engineering rigor to our services — including stateful and transactional (OLTP) systems
Author design documents, uphold standards for clean code and documentation, and review others' designs and deliverables.
Mentor and grow engineers and scientists

Posting record

Report an error

Open 4 monthsWe first saw this posting 125 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records
Live
First seen by us
Jul 6, 2026125 days ago
Recorded sightings
307
Last seen by us
Nov 9, 2026
Employer says posted
Jun 17, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$166K–$240K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 1,354 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 125

Up longer than most. Similar jobs usually come down between day 7 and day 72.

Well past Estée Lauder Companies’s usual: its jobs come down by about day 21.

From 4,738 similar postings that came down, and 17 of Estée Lauder Companies’s. Coming down is not always a hire.

Estée Lauder Companies is hiring

6 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring at a steady pace
  • Takes jobs down at a usual pace
  • 33% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • BigQuery
  • NoSQL
  • FastAPI
  • GCP
Where the posting names them
## Qualifications • BS/BA in a quantitative or technical field (e.g., Computer Science, Statistics, Mathematics, Physics, Engineering, Operations Research, Economics), or equivalent practical experience; a graduate degree is a plus. • 5+ years of experience (3+ with a graduate degree) across Software Engineering, Machine Learning, and/or Data Science. • Strong general software engineering in Python — clean API and service design, data-structure and algorithm proficiency, and real testing discipline — with experience building and operating production-grade services, including stateful / transactional systems and databases (SQL and/or NoSQL). • Experience building and deploying LLM-powered or agentic systems in production (e.g., retrieval-augmented generation, agents and tool use, structured outputs, evaluation, safety) — or a strong production-ML background paired with a clear appetite to work in this space. • Experience deploying and operating systems on a major cloud platform (Google Cloud a plus) with sound data-processing practices at scale. • Uses agentic / AI-assisted development tools, or is eager to adopt them in earnest, with judgment about where they help and how to keep quality high. • A track record of mentorship, a continuous-learning mindset, a bias for simplicity, and a collaborative, shared-ownership working style. Preferred / a strong plus • Genuine classical ML / data science / statistics depth — statistical modeling, hypothesis testing and experimentation, causal inference and incrementality, and predictive modeling. We value this as a way to de-risk future modeling work; it is hard to acquire on the job, so we welcome it even when the immediate work is engineering-focused. • Hands-on experience in NLP, agent frameworks, or advanced statistical methods. • Familiarity with our stack: Google Cloud (Vertex AI, Cloud Run, BigQuery, Firestore, Pub/Sub), async Python (FastAPI), container-based CI/CD, and the Model Context Protocol (MCP). • Experience designing a technical roadmap and leading execution in a business environment. Pay Range:
## Description As a Staff Machine Learning Engineer, you're a player-coach: a strong hands-on contributor who also sets standards, reviews others' work, authors the designs others build against, and mentors the team. You design, build, test, and deploy production AI products and the platform beneath them, and you shape how we build and integrate AI systems — working with engineers, scientists, product managers, and domain experts to turn ambiguous problems into reliable, scalable deliverables. The core of this role is engineering: agentic AI products and their platform, including stateful, transactional services where reliability and data-modeling rigor matter. Classical ML, statistics, and experimentation are valued and let us take on predictive and inference work when the roadmap calls for it — but you may spend long stretches purely on AI-product and platform engineering, so we're looking for someone energized by that work. Responsibilities • Design, build, test, and deploy production agentic / LLM-powered products end-to-end on Google Cloud, along with the shared platform, tooling, and harnesses beneath them. • Bring strong software-engineering rigor to our services — including stateful and transactional (OLTP) systems — across data modeling, concurrency, idempotency, reliability, observability, and testing. • Apply classical ML, statistics, and experimentation where the problem calls for it (predictive modeling, statistical inference, hypothesis testing, causal / incrementality measurement). • Build scalable tools that drive automation across domains such as recommendation and personalization, conversational and customer experiences, and measurement and incrementality. • Author design documents, uphold standards for clean code and documentation, and review others' designs and deliverables. • Mentor and grow engineers and scientists, and support our early-career and student mentorship efforts. • Partner with engineering, product, and domain-expert teams on major cross-functional automation, measurement, and modeling efforts. • At least 80% technical contributor, up to 20% leadership / management. • Actively participate in ELC's diversity and inclusion agenda. ## Qualifications

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About Estée Lauder Companies

People
About 55,000 in 2026, down 4% from the year before.Annual report (SEC Form 10-K)
Company
Listed as EL.

Demand for ML Engineer roles

New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.

Weekly new ML Engineer postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 618, the most 1,085, and the latest week had 859.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

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 As a Staff Machine Learning Engineer, you're a player-coach: a strong hands-on contributor who also sets standards, reviews others' work, authors the designs others build against, and mentors the team. You design, build, test, and deploy production AI products and the platform beneath them, and you shape how we build and integrate AI systems — working with engineers, scientists, product managers, and domain experts to turn ambiguous problems into reliable, scalable deliverables. The core of this role is engineering: agentic AI products and their platform, including stateful, transactional services where reliability and data-modeling rigor matter. Classical ML, statistics, and experimentation are valued and let us take on predictive and inference work when the roadmap calls for it — but you may spend long stretches purely on AI-product and platform engineering, so we're looking for someone energized by that work. Responsibilities • Design, build, test, and deploy production agentic / LLM-powered products end-to-end on Google Cloud, along with the shared platform, tooling, and harnesses beneath them. • Bring strong software-engineering rigor to our services — including stateful and transactional (OLTP) systems — across data modeling, concurrency, idempotency, reliability, observability, and testing. • Apply classical ML, statistics, and experimentation where the problem calls for it (predictive modeling, statistical inference, hypothesis testing, causal / incrementality measurement). • Build scalable tools that drive automation across domains such as recommendation and personalization, conversational and customer experiences, and measurement and incrementality. • Author design documents, uphold standards for clean code and documentation, and review others' designs and deliverables. • Mentor and grow engineers and scientists, and support our early-career and student mentorship efforts. • Partner with engineering, product, and domain-expert teams on major cross-functional automation, measurement, and modeling efforts. • At least 80% technical contributor, up to 20% leadership / management. • Actively participate in ELC's diversity and inclusion agenda. ## Qualifications • BS/BA in a quantitative or technical field (e.g., Computer Science, Statistics, Mathematics, Physics, Engineering, Operations Research, Economics), or equivalent practical experience; a graduate degree is a plus. • 5+ years of experience (3+ with a graduate degree) across Software Engineering, Machine Learning, and/or Data Science. • Strong general software engineering in Python — clean API and service design, data-structure and algorithm proficiency, and real testing discipline — with experience building and operating production-grade services, including stateful / transactional systems and databases (SQL and/or NoSQL). • Experience building and deploying LLM-powered or agentic systems in production (e.g., retrieval-augmented generation, agents and tool use, structured outputs, evaluation, safety) — or a strong production-ML background paired with a clear appetite to work in this space. • Experience deploying and operating systems on a major cloud platform (Google Cloud a plus) with sound data-processing practices at scale. • Uses agentic / AI-assisted development tools, or is eager to adopt them in earnest, with judgment about where they help and how to keep quality high. • A track record of mentorship, a continuous-learning mindset, a bias for simplicity, and a collaborative, shared-ownership working style. Preferred / a strong plus • Genuine classical ML / data science / statistics depth — statistical modeling, hypothesis testing and experimentation, causal inference and incrementality, and predictive modeling. We value this as a way to de-risk future modeling work; it is hard to acquire on the job, so we welcome it even when the immediate work is engineering-focused. • Hands-on experience in NLP, agent frameworks, or advanced statistical methods. • Familiarity with our stack: Google Cloud (Vertex AI, Cloud Run, BigQuery, Firestore, Pub/Sub), async Python (FastAPI), container-based CI/CD, and the Model Context Protocol (MCP). • Experience designing a technical roadmap and leading execution in a business environment. Pay Range: The anticipated base salary range for this position is $119,300.00 to $196,600.00. Exact salary depends on several factors such as experience, skills, education, and budget. Salary range may vary based on geographic location. In addition to base salary, this position is eligible for participation in a highly competitive bonus program as well as participation in the share incentive plan. In addition, In addition to base salary, this position is eligible for participation in a highly competitive bonus program with the possibility for overachievement based on performance and company results. 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, paid leave programs, education-related programs, paid holidays and vacation time, and many others. Many of these benefits are subsidized or fully paid for by the company. Equal Opportunity Employer It is Company's policy not to discriminate against any employee or applicant for employment on the basis of race, color, creed, religion, national origin, ancestry, citizenship status, age, sex or gender (including pregnancy, childbirth and related medical conditions), gender identity or gender expression (including transgender status), sexual orientation, marital status, military service and veteran status, physical or mental disability, protected medical condition as defined by applicable state or local law, genetic information, or any other characteristic protected by applicable federal, state, or local laws and ordinances. The Company will endeavor to provide a reasonable accommodation consistent with the law to otherwise qualified employees and prospective employees with a disability and to employees and prospective employees with needs related to their religious observance or practices. Should you wish to apply for this position or any other position with the Company and you believe you require assistance to complete an application or participate in an interview, please contact USApplicantAccommodations@Estee.com. Michigan Applicants: Persons with disabilities needing accommodations for employment must notify the company in writing of the need for an accommodation within 182 days after the date the person with a disability knew or reasonably should have known that an accommodation was needed. Philadelphia Applicants: Philadelphia's Fair Chance Hiring Law Rhode Island Applicants: The company is subject to chapters 29-38 of title 28 of the general laws of Rhode Island and is therefore covered by the state's workers' compensation law.
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Pay
Pay Range: The anticipated base salary range for this position is $119,300.00 to $196,600.00. Exact salary depends on several factors such as experience, skills, education, and budget. Salary range may vary based on geographic location. In addition to base salary, this position is eligible for participation in a highly competitive bonus program as well as participation in the share incentive plan. In addition, In addition to base salary, this position is eligible for participation in a highly competitive bonus program with the possibility for overachievement based on performance and company results. 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, paid leave programs, education-related programs, paid holidays and vacation time, and many others. Many of these benefits are subsidized or fully paid for by the company.
Location & working pattern

New York, NY, US

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