Sr. Staff, Machine Learning Engineer [L7-1] (Search & Discovery)

1 нед. назад

South KoreaWorldwideLeadOnsite

machine learning

Senior staff machine learning engineer role focusing on Search & Discovery at , based in Seoul, South Korea, for internal employees.

Обязанности

As a Sr. Staff Machine Learning Engineer, you will drive the design, development, and evolution of our end-to-end recommendation systems, placing AI/ML innovation at the core of our recommendation quality. This role encompasses the full lifecycle of recommendations from architecting sophisticated ranking, retrieval, and relevance models to scaling the robust systems that power ’s recommendations. You will partner with global cross-functional teams to own the customer discovery journey, continuously elevating the user experience through rigorous experimentation and the deployment of high-impact algorithms. If you are passionate about leveraging massive, real-time datasets and millions of customer interactions to drive tangible business and customer impact, and you want to solve genui
 
Strongly own the Recommendation service, one of the most critical for to make sure we are wowing customers constantly.
Collaborate tightly with multiple global teams across the company to co-build a world class recommendation system
Mine vast amount of data to gain insights from customer behavior
Develop new Machine Learning models and features to create new recommendation algorithm or improve existing algorithms
Create data jobs to generate Machine Learning features; build and train new models; run experiments to validate and launch new models
Mentor and grow engineers across the teams.

Требования

Bachelor’s degree in Computer Science, Electrical Engineering, Mathematics, Statistics or closely related fields.
Proven ability to derive actionable insights from complex datasets and solve business-critical problems using advanced AI/ML technologies.
Demonstrated experience as a company-wide technical leader, driving cross-functional collaboration to deliver large-scale, high-impact solutions.
8+ years of professional experience in applied AI/ML with large-scale, complex datasets to extract robust features and create reliable machine learning models.
Fast paced self-learner with proven track record of launching successful algorithms that drive measurable business impact.
Professional proficiency in Python and/or Java with relevant industry experience.
Excellent communication skills with professional proficiency in English.

Будет плюсом

Ph.D. or Master degree inComputer Science, Electrical Engineering, Mathematics, Statistics or related science majors
Experience with Recommendation or Search Systems
Experience with LLMs, PLMs, and embedding models
Experience with cloud platforms such as AWS, GCP including services like Vertex AI
Industrial experience working with online serving system working at scale
Excellent communicator with great listening skills, growth mindset and can-do attitude

Как откликнуться

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.
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.
does not discriminate against disabled applicants or those with veteran status. We are proud to offer equal opportunities for all applicants.
Job titles and responsibilities may be subject to change depending on the candidate’s overall experience, etc. This will be communicated to the candidate at the appropriate time before the offer.
Privacy Notice
Your personal information will be collected and managed by as stated in the Application Privacy Notice located below.
https://www.coupang.jobs/en/privacy-policy/
Document Return Policy
This notification is given pursuant to Article 11 (6) of the Fair Hiring Procedure Act.
A job applicant, who has applied but not been finally selected for a position at (the “Company”), may request the Company to return his/her hiring documents submitted pursuant to the Fair Hiring Procedure Act. However, this will not apply where the hiring documents were submitted via the website of the Company or e-mail, or where the job applicant submitted those documents voluntarily without a request from the Company. In addition, if the hiring documents were destroyed due to a natural disaster or any other reasons not attributable to the Company, such documents will be deemed to have been returned to the job applicant.
A job applicant who wishes to request the return of his/her hiring documents pursuant to the main sentence of paragraph 2 above should fill out a “Request for Return of Hiring Documents” [Annex Form No. 3 in the Enforcement Rule of the Fair Hiring Procedure Act] and submit It by email (recruitingops@.com). In such case, within fourteen (14) days from the date of identifying the receipt of the request, the Company will send the hiring documents to the job applicant’s designated address via registered mail. Please be informed that the job applicant is required to pay the postage on the registered mail.
In preparation for a job applicant’s request for the return of hiring documents pursuant to the main sentence of paragraph 2 above, the Company shall retain the original hiring documents submitted by the job applicant for 180 days from the completion of the recruiting process. If no request is made until the end of this period, all of his/her hiring documents will be destroyed immediately in accordance with the Personal Information Protection Act.

Другое

 
본 공고는 재직 임직원을 대상으로 하는 사내 공모 전용입니다. ( 임직원 추천은 Link 로 진행 )
This posting is exclusively for internal employees. (Employee referrals are submitted via the Link )
 
지원 시에는 반드시 첨부된 ‘ 사내 공모 지원서 양식 ’을 작성한 후, 쿠팡 이메일 계정 으로 접수해 주시기 바랍니다.
To apply, please complete the attached ‘ Internal Transfer Request Form ’ and submit it via your email address .
사내 공모 정책: [ Link ]
Internal Transfer Policy: [ Link ]
 
We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did I ever live without ?” Born out of an obsession to make shopping, eating, and living easier than ever, we are collectively disrupting the multi-billion-dollar commerce industry from the ground up and establishing an unparalleled reputation for being leading and reliable force in South Korean commerce.
We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been since our inception. We are all entrepreneurs surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At , you will see yourself, your colleagues, your team, and the company grow every day.
Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional tradeoffs. Join now to create an epic experience in this always-on, high-tech, and hyper-connected world.
 
The Recommendations team optimizes the customer product discovery experience to drive long-term growth. As millions of shoppers encounter recommendations across every screen daily, these interactions account for over half of ’s total sales alongside search, serving as a primary engine for key business initiatives. We focus on enhancing recommendation quality while providing our ranking systems as a platform for stakeholder teams company-wide. By leveraging state-of-the-art AI/ML technologies and building highly scalable systems, we aim to provide a "wow" discovery experience that anticipates customer needs even before they are explicitly expressed.