Currently tracking 7 active AI roles, down 48% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $141k–$325k (avg $222k).
Chewy currently has 18 active AI-related job listings. The majority of these roles are focused on agents, representing 44% of the openings. The company is hiring primarily for engineering positions, with one role in product. Recent hiring activity shows a significant increase, with 13 new AI roles posted in the last 30 days, a 1200% rise from the previous 30-day period.
Chewy currently has 12 active AI-related roles in our index. The most common open titles are: Staff Machine Learning Engineer (2), Business Intelligence Engineer II, Data Scientist III, Director, Software Engineering, Machine Learning Engineer II. Most positions are in Engineering and Product.
Chewy's active AI hiring is concentrated in: agents (50%), serving infrastructure (33%), application (8%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Chewy is hiring AI talent in: United States (12 roles).
Job postings at Chewy most frequently reference: model serving, inference infra, recommender systems, search ranking, llm observability.
In the past 30 days, Chewy has posted 9 new AI-related roles. That is a -36% change versus the prior 30 days (14 → 9).
| Title | Stage | AI score |
|---|---|---|
| Research Scientist III Research Scientist III at Chewy focused on developing and implementing ML-based replenishment models to optimize supply chain outbound fulfillment. Requires a strong background in optimization and machine learning, with experience in cloud environments and deep learning/RL models. | DataPost-train | 7 |
| Machine Learning Engineer II Machine Learning Engineer II at Chewy focused on applying AI/ML to improve big data and predictive applications. Responsibilities include designing, testing, and scaling frameworks, systems, and models, researching and implementing ML algorithms, and developing ML applications from design to deployment. Requires a Master's degree with 2 years of experience or a Ph.D. with 1 year of experience in a relevant quantitative field, with experience in AWS tools, Databricks, R, PySpark, PyTorch, TensorFlow, Docker, and various ML techniques. | Serve | 7 |
| Staff Machine Learning Engineer Staff Machine Learning Engineer at Chewy focused on Sponsored Ads. The role involves deploying ML and data science models to improve shopping experience, selection, ranking, relevance, click-through prediction, bidding, and auction algorithms for onsite and offsite advertising solutions. Key responsibilities include leading models from ideation to production, publishing research, establishing best practices, and mentoring junior scientists. Requires experience in building distributed pipelines, tuning, optimizing, and evaluation, with a background in Sponsored Ads or Advertisement domain, and techniques like predictive models, linear programming, classification, search, ranking, or large-scale embeddings. | Serve | 7 |
| Senior Machine Learning Engineer Senior Machine Learning Engineer at Chewy to work on Sponsored Ads Technology, influencing technical strategy across product search, discovery, relevance, ranking, prediction, and auction. The role involves deploying ML/DL models for ads offerings, optimizing selection, relevance, ranking, click-through prediction, and auction algorithms, and leading new models from ideation to production. Experience with sponsored ads, predictive models, classification, search, ranking, and large-scale embeddings is required. The role also involves publishing research and mentoring junior scientists. | AgentServe | 7 |
| Staff Machine Learning Engineer Staff Machine Learning Engineer at Chewy focused on Sponsored Ads Technology. The role involves deploying ML and data-science models to improve various aspects of the advertising ecosystem, including selection, relevance, ranking, prediction, and auction algorithms. The engineer will lead new models from ideation to production, establish best practices, and potentially publish research. Experience in the advertising domain and building distributed pipelines is required. | Agent | 7 |