Jan 28, 2025
Meet the Rogo team: Aidan Donohue, AI Engineer
We're thrilled to announce that Joseph Kim has joined us as our Head of Applied AI. With his background in AI and search – from MIT to NASA to Google – Joseph brings invaluable experience to help advance Rogo's mission of transforming finance with AI.
From Space Robots to Search: A Journey in Technical Innovation
MIT & NASA
Joseph began his career as a researcher at the MIT Media Lab, working on programmable metamaterials — an interdisciplinary field combining mechanical engineering and computer science. After graduation, he spent four years at NASA as a research scientist, developing systems for aeronautics and robotically assembled space structures. This work involved early applications of deep reinforcement learning, technology that would later influence developments like AlphaGo.
Retail & Industry-Specific AI at Google
In 2017 and 2018, the transformer and BERT papers were released. "Everyone in the ML community had our 'ChatGPT moment' then," Joseph says. Following this development, Joseph joined Google to focus on artificial intelligence. He started in retail search, where he gained insights into industry-specific AI solutions.
"Given the critical impact of online product search on a retailer's revenue and profitability, the lack of technical expertise and investment in this area was shocking," Joseph explains. "Companies relied on thousands of brittle and hand-tuned rules, instead of leveraging the power of big data and machine learning to automatically optimize revenue, and most retailers put very little emphasis on hiring top engineers or developing truly scalable, impactful search solutions. Even with relatively simple ML techniques, Google could outperform in-house solutions by up to 50%. It opened my eyes to how underserved high-stakes industries can be when it comes to applying cutting-edge technology."
Web Search and Gemini at Google
After growing Retail Search from a prototype into one of Cloud's most profitable businesses, Joseph moved to Google's core ranking and ML team for web search. His initial focus was launching BERT to Search's billions of users. "Introducing transformer models into Google Search led to the biggest step-function improvement to search quality ever, and bringing those semantic understanding improvements to Search's billions of users worldwide was a deeply rewarding and humbling experience," Joseph recalls.
Following ChatGPT's launch in late 2022, Joseph joined the Gemini team at Google. His research focused on reinforcement learning with human and machine feedback for improving generative language models.
"The first major wave of AI capabilities was unlocked by the invention of the transformer, enabling super-human semantic understanding at scale. The subsequent release of RLHF and ChatGPT in 2022 further revolutionized the field, enabling sophisticated instruction-following that spawned a host of new applications and products. We are now on the cusp of the third wave: agentic AI. These systems will move beyond simple chat responses to actively participate in complex tasks, working alongside humans in a symbiotic relationship. This shift promises to reshape workflows across numerous sectors, with finance poised to be at the forefront of this transformation."
Why Finance Needs a Search Revolution
Joseph's interest in Rogo stems from his observations about technology in finance. Despite managing trillions of dollars, many financial firms continue to rely on manual processes and fragmented tools.
"I saw the same pattern in finance that I witnessed years ago in retail search," Joseph notes. This insight became clear during the pandemic when a hedge fund offered $20,000 a month for software to track stock discussions on WallStreetBets. "That's a 3-hour project for an engineer that a hedge fund would pay $20,000 a month for, likely because they lack the expertise to even know if it was a 3-hour or 3-month project."
Building the Future of Financial Intelligence at Rogo
At Rogo, Joseph will lead our AI development, focusing on innovations including:
Multi-step reinforcement learning with human and machine feedback
Custom-built hybrid retrieval optimized for LLM prompt packing (RAG++)
Monte Carlo Tree Search for scaling test-time compute
"Finance has always been about rigor and precision," Joseph adds. "At Rogo, we have the opportunity to bring modern AI capabilities to the table."
Join Our Team
If you're interested in applying cutting-edge AI to complex financial problems, we're hiring.
"Within Google Search and Gemini, we tackled some fascinating technical problems. However, the sheer size of Google sometimes meant that there weren't enough GPUs in the world to build our exciting research prototypes into real products. At Rogo, the economics around cost per query are enormously different – and I'm excited to explore a novel solution space and to play a deep role in shaping the future of financial work."
Welcome, Joseph!
Welcoming Our New Head of Applied AI: Joseph Kim
Today marks a defining moment in Rogo’s journey to transform finance with AI.
We’re thrilled to announce that Joseph Kim, one of the world’s leading experts in AI and search, has joined us as our Head of Applied AI. His track record of pioneering technical breakthroughs – from MIT to NASA to Google – sets the stage for Rogo to achieve its bold vision of redefining how knowledge is created, insights are generated, and decisions are made in finance.
From Space Robots to Search Billions: A Journey of System-Level Innovation
MIT & NASA
Joseph began his career journey as a researcher at the MIT Media Lab, delving into programmable metamaterials — an interdisciplinary field combining mechanical engineering and computer science. Joseph joined NASA as a research scientist right after graduation, where he spent four years on pioneering systems for aeronautics and robotically assembled space structures – a challenge that required rethinking how machines learn and adapt in complex environments. This work served as an early introduction into deep reinforcement learning, a nascent form of artificial intelligence that would later serve as the foundation for breakthroughs like AlphaGo.
Retail & Industry-Specific AI at Google
In 2017 and 2018, the transformer and BERT papers were released. “Everyone in the ML community had our ‘ChatGPT moment’ then,” Joseph says. Inspired by the transformative potential of technologies like transformer-based language models, Joseph left NASA and joined Google to focus full-time on artificial intelligence. At Google, he began by tackling AI for retail search – a surprising entry point that shaped his approach to industry-specific solutions.
“Given the critical impact of online product search on a retailer's revenue and profitability, the lack of technical expertise and investment in this area was shocking,” Joseph explains. “Companies relied on thousands of brittle and hand-tuned rules, instead of leveraging the power of big data and machine learning to automatically optimize revenue, and most retailers put very little emphasis on hiring top engineers or developing truly scalable, impactful search solutions. Even with relatively simple ML techniques, Google could outperform in-house solutions by up to 50%. It opened my eyes to how underserved high-stakes industries can be when it comes to applying cutting-edge technology.”
Web Search and Gemini at Google
After two years spent growing Retail Search from a prototype project into one of Cloud’s most profitable businesses, Joseph shifted his attention to solving some of the most difficult machine learning problems within Google’s most important product: web search. As part of the core ranking and ML team, his first focus was launching BERT to Search’s billions of users. “Introducing transformer models into Google Search led to the biggest step-function improvement to search quality ever, and bringing those semantic understanding improvements to Search’s billions of users worldwide was a deeply rewarding and humbling experience,” Joseph recalls.
When ChatGPT launched in late 2022, Joseph joined an elite team within Google focused on bringing the power of Gemini to Google’s billions of users. His most recent research centered on leveraging reinforcement learning with human and machine feedback for improving generative language models, a foundational technique that serves as the foundation for improving LLM capabilities.
“The first major wave of AI capabilities was unlocked by the invention of the transformer, enabling super-human semantic understanding at scale. The subsequent release of RLHF and ChatGPT in 2022 further revolutionized the field, enabling sophisticated instruction-following that spawned a host of new applications and products. We are now on the cusp of the third wave: agentic AI. These systems will move beyond simple chat responses to actively participate in complex tasks, working alongside humans in a symbiotic relationship. This shift promises to reshape workflows across numerous sectors, with finance poised to be at the forefront of this transformation.”
Why Finance Needs a Search Revolution
Joseph’s journey to Rogo was sparked by a simple observation: the world’s most sophisticated financial firms are running on outdated technology. Despite managing trillions of dollars and employing some of the world’s brightest minds, these firms still rely heavily on manual processes and fragmented tools.
“I saw the same pattern in finance that I witnessed years ago in retail search,” Joseph notes. This insight hit home during the pandemic when a hedge fund, willing to pay $20,000 a month, solicited Joseph’s help to build software to track stock discussions on WallStreetBets. “That’s a 3-hour project for an engineer that a hedge fund would pay $20,000 a month for, likely because they lack the expertise to even know if it was a 3-hour or 3-month project.”
Building the Future of Financial Intelligence at Rogo
“Each AI breakthrough – first keyword search, then semantic understanding, now agentic AI – has been predictable in hindsight. Rogo is just as obvious to me as BERT was in 2018,” Joseph explains. “The financial industry is overdue for transformation, and Rogo’s vision, coupled with its focus on domain-specific solutions, is the perfect place to make that happen.”
At Rogo, Joseph will drive our ambitious AI roadmap to build what we believe will become the intelligence layer for modern finance. His vision includes leveraging innovations like multi-step reinforcement learning with human and machine feedback, custom-built hybrid retrieval highly optimized for LLM prompt packing (RAG++), and Monte Carlo Tree Search for scaling test-time compute to tackle some of finance’s most complex challenges. “Finance has always been about rigor and precision,” Joseph adds. “At Rogo, we have the opportunity to bring the best of modern AI to the table.”
A Call to Innovators
Joseph’s hire is a defining moment for Rogo and sets the tone for what’s to come. If you’re passionate about solving complex problems, working with cutting-edge AI, and building the future of an industry, there’s no better time to join Rogo.
“Within Google Search and Gemini, we tackled some of the most fascinating and highly rigorous technical problems. However, the sheer size of Google sometimes meant that there weren’t enough GPUs in the world to build our exciting research prototypes into real products. At Rogo, the economics around cost per query are enormously different – and I’m super excited to explore a novel solution space and to play a very deep role in shaping the future of financial work.”
Welcome, Joseph! We’re beyond excited for the journey ahead.

Gabe Stengel
CEO, Co-Founder
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