Currently tracking 7 active AI roles, up 19% versus the prior 4 weeks. Primary focus: Serve · Engineering. Salary range $164k–$226k (avg $195k).
Upstart currently has 12 active AI-related job listings. The majority of these roles are focused on serving infrastructure, accounting for 33% of the openings, followed by agents at 25%. Engineering is the dominant function, with 11 out of the 12 roles. Frequent tech tags include model serving, inference infrastructure, and recommender systems, suggesting a focus on deploying and optimizing AI models.
Upstart currently has 7 active AI-related roles in our index. The most common open titles are: Principal Applied Scientist, Principal Product Manager, Agentic Platform, Principal Software Engineer, Machine Learning Simulations , Senior Engineering Manager, Marketplace, Senior Engineering Manager, Offer Delivery. Most positions are in Engineering and Product.
Upstart's active AI hiring is concentrated in: application (43%), agents (29%), serving infrastructure (29%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Job postings at Upstart most frequently reference: model serving, recommender systems, inference infra, agent orchestration, tool use.
In the past 30 days, Upstart has posted 1 new AI-related role.
| Title | Stage | AI score |
|---|---|---|
| Principal Engineer, LLM Principal Engineer for Upstart's GenAI Core Platform team, responsible for technical leadership, roadmap definition, architecture, and adoption strategy for a new GenAI platform. The role focuses on enabling safe, efficient, and responsible LLM use across the company, identifying and solving systemic technical risks, and establishing operational standards for GenAI integrations. This includes building scalable systems for model inference, orchestration, compliance, and accelerating engineer productivity. | ServeAgent | 9 |
| Staff+ Machine Learning Engineer Staff+ Machine Learning Engineer at Upstart, focusing on building the foundational technology for ML platform. This role involves creating scalable tools and systems to accelerate model development, including a unified embeddings platform, streamlined feature engineering, automated continuous learning, and scaled training pipelines. The goal is to improve predictive accuracy and multiply the effectiveness of ML teams. | ServeData | 8 |
| Principal Software Engineer, Machine Learning Simulations Principal Software Engineer to build and operate an MLOps platform for ML model inference, process automation, model deployment, and observability, as well as a marketplace simulation platform for ML and Finance teams at Upstart, a leading AI lending marketplace. | ServeEval Gate | 7 |