Robinhood
Fintech · Retail trading
- HQ
- Palo Alto, US
- Founded
- 2013
- Website
- robinhood.com
Robinhood currently has 11 active job listings for AI-related roles. The company is primarily hiring for roles focused on agents and serving infrastructure, each representing 36% of the open positions. Engineering is the dominant function, with 10 of the 11 roles listed. Frequent tech tags include model serving, fine-tuning, and inference infrastructure, suggesting a focus on deploying and optimizing AI models. Over the last 30 days, Robinhood has added 7 new AI roles, a 133% increase compared to the previous 30-day period.
Fintech · Retail trading
Currently tracking 7 active AI roles, up 85% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $118k–$350k (avg $228k).
Robinhood currently has 12 active AI-related roles in our index. The most common open titles are: Software Engineer (2), Machine Learning Engineer, Manager of Response, Automation, Intelligence & Detection Engineering, Privacy Engineer, Senior Software Engineer. Most positions are in Engineering and Product.
Robinhood's active AI hiring is concentrated in: agents (42%), serving infrastructure (33%), application (17%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Robinhood is hiring AI talent in: United States (7 roles), Canada (2 roles).
Job postings at Robinhood most frequently mention: Machine Learning, Testing Practices, Technical Documentation, Software Engineering, Real-Time Systems.
In the past 30 days, Robinhood has posted 7 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Machine Learning Engineer Robinhood is seeking a Machine Learning Engineer to join their AI Research and Development team. The role focuses on implementing and evaluating ML algorithms, developing scalable models for ranking and recommendation systems, and applying techniques like collaborative filtering, content-based filtering, hybrid models, Learning to Rank (LTR), reinforcement learning, and multi-armed bandits. The engineer will also design and conduct A/B tests, analyze experimental data, collaborate with cross-functional teams, and build reusable ML libraries. | AgentPost-train | 8 |