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.
Fintech · AI-native lending (FICO alternative)
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 |
|---|---|---|
| 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 |
| Senior Manager, Machine Learning Upstart is seeking a Senior Manager, Machine Learning to lead a small, nimble team of individual contributors. This is a highly technical player-coach role where the manager will spend roughly 50/50 split between technical execution and management. The role involves leading ML innovation for new products, building core models, optimizing mature models, and translating model predictions into business impact within the fintech domain. The team focuses on generalist ML leaders who can be deployed to areas of high impact, including new initiatives and scaling existing models. | ShipData | 8 |
| Principal Applied Scientist This role focuses on defining the long-term technical direction for Upstart's offer optimization and conversion modeling systems. The Principal Applied Scientist will work across teams to ensure models and optimization systems account for downstream effects, marketplace constraints, and customer outcomes. The work involves structuring ambiguous problem spaces, designing solutions for multi-stage customer journeys, and providing technical oversight. It sits at the intersection of operations research, optimization, causal machine learning, and production decision systems. | Agent | 7 |
| 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 |