Okay, I've searched for Senior Machine Learning Engineer roles in Bellevue, WA within the e-commerce industry, for full-time positions, requiring 3 years+ experience. I have found 47 positions for you.

Sure. Here's the analysis:

Job Analysis:

This Senior Machine Learning Engineer role at Chewy is fundamentally about leveraging advanced machine learning and data science techniques to optimize and revolutionize the sponsored advertising experience within a large-scale e-commerce ecosystem. The candidate is expected not only to build and deploy sophisticated predictive models—covering CTR prediction, relevance ranking, dynamic bidding, and auction mechanisms—but also to influence the overall technical strategy for ad products that impact both onsite and offsite channels. The responsibilities demand a full lifecycle ownership: from ideation, rigorous experimentation, productionization, to ongoing model performance optimization, all at Chewy's scale. The role also involves translating complex research findings into clear business recommendations and communicating with diverse stakeholders, from engineering teams to senior leadership. Essential qualifications reflect the complex problem space—strong proficiency in applied mathematics, statistics, optimization, and distributed systems is critical. Prior experience in advertising systems or e-commerce adds important context, given the need to deliver targeted, relevant ads that resonate with pet parents while balancing business goals for brand owners and Chewy. Success in this role will be measured by the ability to launch innovative ad offerings that maximize customer engagement and revenue, mentor junior talent, maintain high scientific standards, and navigate cross-functional dynamics in a mission-driven but technically challenging environment.

Company Analysis:

Chewy occupies a distinct position as a fast-growing and mission-oriented e-commerce leader specializing in pet products—an industry where emotional connection and customer trust are paramount. Their culture is clearly centered on customer obsession, innovation, and personalization, blending the warmth of a neighborhood pet store with the technological rigor of a cutting-edge digital platform. This ethos suggests a workplace that values agility, collaboration, and passion for pets, fostering both technical excellence and empathy. For a Senior Machine Learning Engineer, this means opportunities to create meaningful impact that improves the lives of pet parents and their pets, beyond revenue metrics. The Sponsored Ads team's work supports Chewy’s broader strategic imperative of enhancing customer experience while driving a critical revenue stream via advertising innovation. Situated likely as a senior IC or technical leader within this specialized team, the role offers high visibility with leadership and cross-team interactions, demanding both technical depth and strong communication skills. Given Chewy’s growth trajectory and emphasis on advanced AI techniques (including LLMs and generative AI), this position is a strategic hire poised to scale and sophisticate Chewy’s ad ecosystem, balancing business needs with cutting-edge ML research and scalable production deployment.

Absolutely. Here are some mock interview questions that could come up:

• Behavioral: Tell me about a time when you had to translate complex machine learning results into clear business recommendations for non-technical stakeholders. How did you approach it and what was the outcome?
• Behavioral: Describe an instance where you led a machine learning project from thesis to production. What challenges did you face and how did you ensure its success at scale?
• Behavioral: How have you mentored junior data scientists or engineers in your previous roles? Can you provide an example where your guidance impacted their performance or project outcomes?
• Behavioral: Discuss a situation where you had to collaborate across multiple teams (e.g., product, engineering, data science) to deliver an advertising solution. What strategies did you use to manage differing priorities?
• Technical: Walk me through your approach to designing and deploying a click-through rate prediction model for a sponsored ads platform. What features and algorithms would you consider critical?
• Technical: How would you optimize an auction algorithm for sponsored ads to balance advertiser ROI and user experience? What data science techniques and business considerations come into play?
• Technical: Explain your experience building and tuning distributed machine learning pipelines. What tools and frameworks have you used, and how do you monitor model performance at scale?
• Technical: Chewy is exploring the use of large language models (LLMs) and generative AI for ads relevance and recommendations. How would you evaluate and integrate these technologies into an existing advertising stack?
• Situational: Imagine you deploy a new bidding model that improves revenue but leads to a drop in user engagement metrics. How would you approach analyzing, communicating, and resolving this issue?
• Situational: Suppose a product leader requests a solution that contradicts your data-driven insights or ML model predictions. How would you handle this disagreement while maintaining alignment?
• Situational: You discover a junior team member’s model has performance issues after deployment affecting ad relevance. What steps would you take to address both the technical problem and coach the team member?
• Company Fit: What attracts you specifically to Chewy’s mission of serving pet parents, and how do you see your work in sponsored ads aligning with this mission?
• Company Fit: Given Chewy’s focus on both customer personalization and scaling technology, how do you balance innovation with delivering reliable, production-ready machine learning solutions?
• Company Fit: How do your personal values resonate with a company that emphasizes passionate pet people and a customer-obsessed culture?
• Questions for Interviewer: Can you describe how the Sponsored Ads team collaborates with other departments such as Product, Engineering, and Marketing to drive ad innovations?
• Questions for Interviewer: What are the most significant challenges the Senior Machine Learning Engineer will face in the first six months?
• Questions for Interviewer: How does Chewy foster continuous learning and professional development for ML engineers in terms of mentorship and exposure to cutting-edge research?