Research Intern
Posted 27 May 2026
Advertised as “Research Intern, Agent RL Training”
BranchFactor Summary
The original posting with the fluff stripped out
- Management level
- Individual contributor
- Employment
- On-Site
- Contract
- Internship
No salary listed for this role.
About NewsBreak
Founded in 2015, NewsBreak is the Content Intelligence platform shaping the future content economy. With over 40 million monthly active users, our flagship platform delivers highly personalized local news and information powered by advanced AI, recommendation systems, and adtech.
Recognized by Fast Company as #32 on the Top Workplaces for Innovators, we're proud to be Great Place to Work® certified and home to a dynamic team of technologists, product innovators, and business leaders who are passionate about solving meaningful challenges at scale.
Together, we reached unicorn status in 2021, and we remain committed to continuing this high-growth trajectory with the right team to fulfill our mission: building the infrastructure layer for content intelligence.
If you’re inspired to dream big, innovate fast, and make a difference, we’d love to hear from you! For more information, visit www.newsbreak.com/about
About the Role
We are looking for a Research Intern to join our Agent RL Training team. You will be paired with a full-time employee as your mentor, working together to explore, from zero to one, how to apply large language models to NewsBreak’s core business, including content understanding, recommendation, agentic web browsing, and autonomous multi-step task completion.
This is a hands-on research role. You are expected to independently drive experiments, propose novel ideas, and iterate quickly. We value self-starters with deep intellectual curiosity and the drive to push boundaries in LLM post-training and agent capabilities.
Location: Onsite in Mountain View, CA office
What You’ll Work On
- Collaborate with your full-time mentor to identify high-impact research directions for applying LLMs to NewsBreak’s products
- Independently run end-to-end SFT experiments on LLM-based agents, and assist with RL-related exploration such as reward design and training iteration
- Curate and build high-quality training datasets: instruction-following, preference pairs, agent trajectories, and synthetic data
- Contribute to public publications; we encourage and support top-venue submissions during your internship
What We’re Looking For
Requirements
- Highly motivated and committed: willing to put in extra hours when needed to push projects across the finish line
- Genuine passion for research: you read papers for fun, tinker with models on weekends, and care deeply about advancing the field