Machine Learning Engineer III, Sponsored Ads at Chewy

Bellevue, Washington, United States -

Full Time

Start Date

Immediate

Expiry Date

25 Jan, 26

Salary

249000.0

Posted On

27 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Deep Learning, Data Science, Optimization, Predictive Models, Linear Programming, Classification, Search, Ranking, Large-Scale Embeddings, AWS, SageMaker, Personalize, E-Commerce, Advertising

Industry

Retail

Description

Our Opportunity: The Chewy Sponsored Ads team is looking for a Senior Machine Learning Engineer in Bellevue, WA to help launch various innovative ads-offerings for our sponsored advertisement initiatives. As advertising is a critical component of our e-commerce ecosystem, this role will help provide a critical revenue stream to the company! As a member of our Sponsored Ads development team, you will influence technical strategy across product, search, and discovery, as well as the relevance, ranking, prediction, and auction of a large selection of our sponsored ads offering (both onsite and offsite). You’ll be at the forefront of leading technology business impact, applying machine learning and deep-learning models that will influence selection, relevance, ranking, click-through prediction modelling, auction-dynamics, keywords recommendation, campaign optimization, ads channel performance, ads performance maximization, and wide array of engaging data-science methodologies (including but not limited to LLMs and generative AI). Sponsored Ads composes a win-win ecosystem for shoppers, brand owners, and Chewy! Our Pet Parent customers are offered a range of alternate options to help them choose and learn about new products, new brands, new promotions, and different price points. Brand owners and advertisers get to showcase their product offerings in the front row for their target audience (proud pet parents) and improve their reach. Come be part of the Sponsored Ads team’s impactful journey at Chewy! What you'll do: Deploy machine learning and data-science to simplify shopping experience for pet-parents, to improve reach and discovery of new products of Chewy vendors and helping build a mutually beneficial ecosystem. Directly influence and collaborate with Product and Engineering leaders to evolve solutions using applied science to improve selection, ranking, relevance, deal-offerings, click through prediction models, dynamic bidding, and auction algorithms for Chewy onsite and offsite advertising solutions. Lead new models from ideation to experimentation, and eventually to production delivery to build and improve Chewy products offerings and advance applied science applications. Publish research papers in leading ML/AI/Advertising conferences solving problems for scale using innovative modelling. Establish high bar on model performance, establish applied-science implementation standard methodologies and mentoring junior scientists. Deploy solutions at Chewy scale improving overall customer engagement and value for Pet Parents. Formalizing proposals and communicating verbally and in writing to Chewy Senior Leadership and business customers with varying levels of technical knowledge, educating them about our research, as well as sharing insights and recommendations. What You'll Need: An advanced degree (M.S., PhD, or equivalent experience) in Operations Research, Statistics, Applied Mathematics, Data Science or related field or proven experience for at least 3 years crafting optimization and machine learning solutions for large scale applications. Ability to understand and apply sophisticated mathematics and DS methodologies. Experience in building distributed pipeline, tuning, optimizing and evaluation. Experience with Sponsored Ads or Advertisement domain. Experience with multiple techniques that include Predictive Models (Time Series and Regression), Linear Programming, and Classification, Search, Ranking or large-scale embeddings. Ability to translate complex data sets and research into simple business recommendations. Bonus: Experience in e-commerce or retail. Prior experience in Advertising systems a huge plus. Experience with ML Services in AWS (SageMaker, Personalize) or equivalent. The specific salary offered to a candidate may be influenced by a variety of factors including but not limited to the candidate’s relevant experience, education, and work location. In addition, this position is eligible for 401k and a new hire and annual equity grant. We offer different types of insurance and benefits, such as medical/Rx, vision, dental, life, disability, hospital indemnity, critical illness, and accident. We offer parental leave, family services benefits, backup dependent care, flexible spending accounts, telemedicine, pet adoption reimbursement, employee assistance program, and many discounts including 10% off pet insurance and 20% off at Chewy.com. Exempt salary team members have unlimited PTO, subject to manager approval. Team members will receive six paid holidays per year. Team members may be eligible for paid sick and family leave in compliance with applicable state and local regulations. Base Salary Range $155,500—$249,000 USD Chewy is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, gender, citizenship, marital status, religion, age, disability, gender identity, results of genetic testing, veteran status, as well as any other legally-protected characteristic. If you have a disability under the Americans with Disabilities Act or similar law, and you need an accommodation during the application process or to perform these job requirements, or if you need a religious accommodation, please contact CAAR@chewy.com. To access Chewy's Customer Privacy Policy, please click here. To access Chewy's California CPRA Job Applicant Privacy Policy, please click here.

Responsibilities

Deploy machine learning and data-science to enhance the shopping experience for pet parents and improve product discovery. Lead the development of new models from ideation to production delivery, collaborating with product and engineering teams.