Job Description

Our Opportunity:

Marketing is a critical component of the ecommerce ecosystem and provides the core of the customer’s first experience at Chewy. At Chewy, we are seeking a Staff Machine Learning Engineer to serve as a technical anchor for our Marketing Science and Operations Technology team (Martech). This role is pivotal in shaping the future of our machine learning capabilities and infrastructure. As a Staff MLE, you will provide hands-on technical leadership—designing, building, and deploying scalable ML systems—while mentoring engineers and guiding architectural decisions across the organization. You’ll partner closely with product engineering, data science, and leadership to ensure our models and platforms deliver measurable impact to users and the business.

This is both a strategic and execution-focused role : you’ll balance deep technical contributions with cross-functional collaboration, setting best practices for experimentation, deployment, and monitoring of ML systems. The ideal candidate is not only highly skilled in building and scaling production ML but also thrives in shaping engineering culture and helping the team grow through mentorship and influence.

What you'll do:

• You will lead new models from conceptualization to experimentation, and eventually to production delivery to improve Chewy products offerings and advance applied science applications.


• Establish high bar on model performance, establish applied-science implementation standard processes and mentoring junior scientists.


• Deploy solutions at Chewy scale improving overall customer engagement and value for Pet Parents and marketers.


• 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:

• 7+ years of experience in applied machine learning, data science, or ML engineering, with at least 2+ years working at Staff/Principal level or equivalent technical leadership capacity.


• Proven track record of designing, building, and deploying ML models into production at scale.


• Strong software engineering foundations (Python, Java/Scala, or similar) with experience in backend or platform development.


• Expertise in ML lifecycle tooling using Databricks with MLflow and Airflow.


• Deep knowledge of data pipelines, feature stores, and distributed training/serving systems.


• Ability to set technical direction and influence cross-functional teams through architecture reviews, design documents, and mentorship.


• Strong communication skills and the ability to partner effectively with product managers, software engineers, and leadership

Bonus:

• Experience in e-commerce or retail.


• Exposure to front-end or product-facing integration of ML features.


• Prior experience mentoring and growing engineers into more senior technical roles.


• Advanced degree (MS or PhD) in Computer Science, Machine Learning, Statistics, or a related field.

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