Currently tracking 23 active AI roles, up 90% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $161k–$331k (avg $225k).
Instacart currently has 35 active AI-related job listings. The majority of these roles, 60%, are focused on agents, with application roles making up another significant portion at 31%. Engineering is the most frequent function hiring for these positions, followed by Product. The company is actively seeking talent in the United States and Canada. Frequent tech tags include recommender systems, search ranking, and model serving, suggesting a focus on core AI applications and their deployment. Over the last 30 days, Instacart posted 8 new AI roles, representing a 43% decrease compared to the previous 30-day period.
Instacart currently has 42 active AI-related roles in our index. The most common open titles are: AI Solutions Architect (2), Director of Product, Agentic Commerce (2), Knowledge Strategist Team Lead, Governance (2), Senior Data Scientist (I & II) (2), Senior Data Scientist - Shopping Experience (Search) (2). Most positions are in Engineering and Product.
Instacart's active AI hiring is concentrated in: agents (57%), application (24%), data (14%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Instacart is hiring AI talent in: United States (31 roles), Canada (11 roles).
Job postings at Instacart most frequently reference: model serving, rag, agent orchestration, recommender systems, llm observability.
In the past 30 days, Instacart has posted 24 new AI-related roles. That is a +167% change versus the prior 30 days (9 → 24).
| Title | Stage | AI score |
|---|---|---|
| Senior Machine Learning Engineer II, Ads Response Prediction Lead research and development of pCTR and conversion prediction models, focusing on calibration, debiasing training data, and advancing accuracy. Contribute to next-generation Multi-Domain Multi-Task (MDMT) models, sequence modeling initiatives like TIGER, and Foundation Models for ads ranking. Formulate ambiguous problems into research directions with clear evaluation criteria. | Post-trainAgent | 9 |
| Senior Machine Learning Engineer II, Ads Response Prediction Lead research and development of pCTR and conversion prediction models, focusing on improving calibration, reducing training data biases, and advancing model accuracy. Design and implement debiasing techniques, contribute to next-generation Multi-Domain Multi-Task (MDMT) models, and drive sequence modeling initiatives like TIGER. Collaborate on Foundation Models and formulate ambiguous modeling problems. | Post-train |
| 8 |