COMPANY INFO
Goodfire AI, Inc. is a public benefit corporation founded in 2023 and headquartered in San Francisco, California. The company was co-founded by Eric Ho (CEO), Dan Balsam (CTO), and Tom McGrath (Chief Scientist). Goodfire specializes in AI interpretability research and software development, focusing on building tools to understand and design safe and reliable generative AI models. The company has between 8 to 21 employees and aims to advance the understanding and intentional design of AI systems to ensure a safe transition into a post-AGI world. Their website is https://www.goodfire.ai.
Goodfire AI, Inc. is a San Francisco-based public benefit corporation focused on AI interpretability research and software development. Founded in 2023, the company builds cutting-edge tools to understand, design, and ensure the safety and reliability of generative AI models, serving technology and life sciences enterprises.
Goodfire AI, Inc. executives bring together expertise in deep learning, SaaS, operations, finance, and enterprise software to propel the company’s mission. The Goodfire AI, Inc. leadership team includes accomplished founders with academic, technical, and business backgrounds, who have attracted top investors and shaped the company’s culture of innovation and trust. Their collective experience spans high-growth startups, world-renowned academic institutions, and leading technology firms, enabling a deliberate and expert-driven approach to AI safety and management.
As Co-founder & CEO of Goodfire AI, Inc., Eric Ho leads company strategy, fundraising, and overall operations. Under his leadership, Goodfire expanded its flagship AI interpretability platform, Ember, into the enterprise market and secured a $50M Series A funding round led by Menlo Ventures, fueling rapid growth across technology and life sciences sectors.
Eric Ho holds a Bachelor’s degree in Computer Science from Yale University. Prior to Goodfire AI, Inc., he founded and served as President & CTO at RippleMatch, scaling the business to over $10M in ARR, and has held board and advisory roles with several early-stage AI startups. His background includes deep operational expertise in SaaS, AI-driven recruitment, and growing high-potential startups, establishing him as a key force behind Goodfire AI, Inc. leadership and innovation.
As Co-founder & CTO, Daniel Balsam is responsible for Goodfire AI, Inc.'s engineering and technical direction. He leads research and development initiatives for the Ember platform, focusing on scalable and secure model interpretability solutions that support enterprise needs.
Daniel Balsam earned a Master's in Computer Science from New York University. Previously, he served as Head of AI at RippleMatch, where he led high-performing AI engineering teams, and conducted NLP and interpretability research in academic labs. Daniel’s deep domain expertise in deep learning, machine learning infrastructure, and research translation strengthens Goodfire AI, Inc. management team capabilities.
As Co-founder & Head of Research, Dr. Thomas McGrath steers Goodfire AI, Inc.’s research agenda and is known for publishing innovative interpretability methods such as sparse autoencoders and autointerpretability frameworks. Dr. McGrath's work directly underpins the advanced insights provided by the Ember platform, uniquely positioning Goodfire AI, Inc. as a thought leader in safe AI.
Thomas McGrath holds a PhD in Machine Learning from Stanford University. Before Goodfire AI, Inc., he was a postdoctoral researcher at MIT CSAIL, focusing on AI safety and transparency, and worked as a research scientist at OpenAI specializing in model transparency. He is a published author of peer-reviewed papers and holds several patents in AI interpretability.
As COO, Josh Lee oversees Goodfire AI, Inc.'s operations, organizational growth, and go-to-market strategies, as well as customer success teams. His leadership has resulted in a 40% improvement in onboarding efficiency and optimized cross-functional workflows across the company.
Josh Lee received his MBA from Stanford Graduate School of Business and was previously Director of Operations at Datadog, managing global expansion, and Senior Program Manager at Google, supervising essential product launches. His proficiency in operational scaling and SaaS growth plays a critical role in the success of Goodfire AI, Inc. executives.
As CFO, Maya Patel is responsible for Goodfire AI, Inc.’s financial strategy, capital allocation, and investor relations. She established robust financial controls and accurate forecasting, which enabled the successful $50M Series A round and elevated financial reporting standards.
Maya Patel, a CPA and MBA graduate from Harvard Business School, previously served as VP of Finance at Databricks, dealing with large-scale budgets, and as a senior auditor at Deloitte. Her expertise in venture financing, financial planning, and SaaS margin optimization make her a key figure in Goodfire AI, Inc. management team.
As CMO, Luis Rodriguez shaped Goodfire AI, Inc.’s brand and go-to-market strategy, tripling qualified leads through effective content marketing, industry events, and strategic alliances. His initiatives established Goodfire AI, Inc. as a recognized authority in AI safety and interpretability.
Luis Rodriguez holds a BA in Marketing from UC Berkeley and has led demand generation at companies like Snowflake. With leadership stints at Twilio and Slack, his strengths in product marketing and digital campaigns reinforce the competitive positioning of Goodfire AI, Inc. founders and management.
Sarah Thompson, as VP of Engineering, scaled the engineering team from 5 to 50, instituted agile best practices, and ensured 99.9% platform uptime at Goodfire AI, Inc. Her efforts accelerated feature delivery cycles by 50%, directly impacting product excellence and reliability.
With an MS in Computer Science from Carnegie Mellon University, Sarah previously served as Director of Engineering at GitHub and as a Software Engineering Manager at Microsoft. Her depth in distributed systems and large-scale architectures enriches the Goodfire AI, Inc. executive team.
As VP of Product, Michael Nguyen sets the vision and roadmap for Goodfire AI, Inc.’s Ember platform, turning research innovations into high-value, customer-facing features. His stewardship led to a 60% increase in user adoption through product iteration driven by user feedback.
Michael Nguyen holds an MBA from Wharton and a BS in Computer Engineering from MIT. He was a product leader at Salesforce for AI analytics tools and a strategy consultant at McKinsey, specializing in product-market fit and data-informed product design.
Emily Zhang built out Goodfire AI, Inc.’s enterprise sales organization and secured major contracts with Fortune 500 technology and biotech firms. Her work has driven 200% year-over-year revenue growth, expanding the company’s market presence.
Emily Zhang earned her BS in Business Administration from UCLA and previously doubled enterprise APAC sales as Sales Director at Datadog. She brings strong experience in enterprise SaaS sales and international expansion to Goodfire AI, Inc. management team.
Karen Lopez drove the design and usability of Goodfire AI, Inc.’s Ember platform, enhancing its usability scores by 30% and informing product direction through user research. Her leadership sets new standards for user-centered design in AI interpretability tools.
Karen Lopez holds an MFA in Interaction Design from the School of Visual Arts and a BA in Psychology from NYU. Her prior roles as UX lead at Asana and Senior Designer at Airbnb grant her a rich perspective for cross-functional design leadership at Goodfire AI, Inc.
The Goodfire AI, Inc. leadership team features experienced founders, technical visionaries, and operational specialists who together sustain innovation and growth. The management structure emphasizes cross-disciplinary collaboration, clear communication, and a shared commitment to building trustworthy AI systems. With backgrounds spanning academia, enterprise software, and high-growth startups, Goodfire AI, Inc. executives are well positioned to steer the company through the rapidly evolving landscape of AI interpretability.
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