Interested in this AI/ML Engineer role at Coupang?
Apply Now →About This Role
Coupang is one of the largest and fastest growing e-commerce platforms on the planet. We are on a mission to revolutionize everyday lives for our customers, employees, and partners. We solve problems no one has solved before to create a world where people ask, "how did we ever live without Coupang?" Coupang is a global company with offices in Beijing, Los Angeles, Seattle, Seoul, Shanghai, and Silicon Valley. We are on a mission to create a world without tradeoffs for our customers as we Aim High and Find a Way to Wow our Customers. We have been named one of the "50 Smartest Companies in the World" by MIT Technology Review and "30 Global Game Changers" by Forbes.
Job Overview
Search & Discovery is the most critical customer facing experience within Coupang, relevantly match-making the billions of products to customer intent. We are building the next-generation infrastructure to sustain the hypergrowth of the business for the coming years. We are looking for an experienced and passionate engineer leader that can drive this effort across the stack, including serving, pipelines, and machine learning.
The desired candidate can dive deep into underlying components, design and optimize the stack end-to-end and be a role model for building high-quality machine learning systems and delivering results with grit. Key to this position's success will require the ability to understand business needs and work backwards to develop technical solutions while working effectively with leaders of individual teams and align technical directions with key stakeholders.
This role will involve working closely with Search senior leadership (VP, Sr. Directors) and will offer the autonomy to identify and solve key Search problems and explore innovations in various areas like deep learning and large language modeling, with a specific focus to improve search relevance and quality.
Key Responsibilities
Build end-end Search & Discovery systems and help design the next-generation AI products to support the business growth
Have strong execution with the ability to drive key developments and overcome technical blockers
Ensure solid ML design and operational excellence
Be metrics driven and can identify big opportunities
Build strong collaborations with partner teams
Recruit and develop world-class talent
Basic Qualifications
6+ years of industry experience in technology companies.
Have a broad and deep understanding of key technology areas including information retrieval, deep learning, large language modeling, data processing, real-time serving.
Solid track record of delivering large and complex systems with big business impacts.
Strong design and problem-solving skills.
Excellent communications and collaborations across teams and across functionalities.
Preferred Qualification
Working experiences on search and recommendations systems.
Search relevance and query understanding
Technical Lead or Manager of teams
Pay & Benefits
Our compensation reflects the cost of living across several US geographic markets. At Coupang, your base pay is one part of your total compensation.
The base pay for this position ranges from $174,000K/year to $299,000K/year. Pay is based on several factors including market location and may vary depending on job-related knowledge, skills, and experience.
General Description of All Benefits
- Medical/Dental/Vision/Life, AD&D insurance
- Flexible Spending Accounts (FSA) & Health Savings Account (HSA)
- Long-term/Short-term Disability
- Employee Assistance Program (EAP) program
- 401K Plan with Company Match
- 18-21 days of the Paid Time Off (PTO) a year based on the tenure
- 12 Public Holidays
- Paid Parental leave
- Pre-tax commuter benefits
- MTV - [Free] Electric Car Charging Station
General Description of Other Compensation
"Other Compensation" includes, but is not limited to, bonuses, equity, or other forms of compensation that would be offered to the hired applicant in addition to their established salary range or wage scale.
Recruitment Process and Others
Recruitment Process
- Application Review - Phone Interview - Onsite (or Virtual Onsite) Interview – Offer
- The exact nature of the recruitment process may vary according to the specific job and may be changed due to scheduling or other circumstances.
- Interview schedules and the results will be informed to the applicant via the e-mail address submitted at the application stage
Details to Consider
- This job posting may be closed prior to the stated end date for application if all openings are filled.
- Coupang has the right to rescind an offer of employment if a candidate is found to have submitted false information as part of the application process.
- Those eligible for employment protection (recipients of veteran's benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws.
Privacy Notice
- Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice located below: https://www.coupang.jobs/privacy-policy/
Coupang is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to actual or perceived race (including traits historically associated with race, including but not limited to hair texture and protective hair styles), color, religion, religious creed (including religious dress and grooming practices), sex or gender (including pregnancy, childbirth, breastfeeding, and medical conditions related to pregnancy, childbirth or breastfeeding), gender identity, gender expression, sexual orientation, ,ancestry, national origin (including language use restrictions), age (40 and over), physical or mental disability, medical condition, genetic information, HIV/AIDS or Hepatitis C status, family status (including but not limited to marital or domestic partnership status), military or veteran status, use of a trained dog guide or service animal, political activities or affiliations, ancestry, citizenship, family and medical leave status, status as a victim of any violent crime, or any other characteristic or class protected by the laws or regulations in the locations where we operate. Coupang is also committed to providing a safe work environment for its employees and its consumers.
If you need assistance and/or a reasonable accommodation in the application of recruiting process due to a disability, please contact us at [email protected]*.*
Job Requisition ID: R0079238
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 9,653 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Coupang, 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 11,857 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $228,700.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. 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: $272,275; VP: $235,000.
Coupang AI Hiring
Coupang has 2 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Seattle, WA, Mountain View, CA, US.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 roles, $210,000 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 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. 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 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). 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 (193) are outnumbered by mid-level (4,500) and senior (3,455) 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 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 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 $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. 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 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 (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 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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