Catalyst Labs
About Us
Catalyst Labs is a leading talent agency with a specialized vertical in Applied AI, Machine Learning, and Data Science. We stand out as an agency that’s deeply embedded in our clients’ recruitment operations. We partner directly with AI-first startups building products powered by LLMs, generative AI, intelligent automations; established tech companies scaling their ML infrastructure, recommendation systems, and data platforms; and enterprise innovation teams integrating AI into traditional domains such as finance, healthcare, and logistics. Our Client
Is reimagining how knowledge is shared. They’re building a new medium for human connection: interactive digital minds that people can talk to, learn from, and be guided by. The internet gave us static profiles and infinite feeds; they create something profoundly different: living, interactive identities that carry your voice, judgment, and worldview into every conversation. People don’t just read about you, they experience how you think. Their mission is bold and generational in scope: Make human wisdom abundant, personalized, and discoverable. Preserve legacies, unlock opportunity, and scale brilliance across generations. Trusted by thousands of the world’s most brilliant thinkers from Simon Sinek to Arnold Schwarzenegger and have tripled revenue, users, and mind interactions in the past six months, all organically. Backed by Sequoia Capital, Founders Fund, Lux Capital, and visionary angels including Michael Ovitz, Gokul Rajaram, and Olivia Wilde, they’re now scaling rapidly toward the next frontier of AI-driven human expression. Location
Jackson Square, San Francisco Work type
Fully on-site, 5 days a week Compensation
Above-market base + equity + benefits Visa
Sponsorship available only for candidates already in the United States The Role
As an Applied AI Engineer, you’ll help architect the foundation of next-generation Mind Architecture, the system that powers how digital minds learn, reason, and express individuality. Unlike traditional RAG systems that treat data as a static collection of documents, we build rich, hierarchical knowledge graphs that mirror how real experts think capturing not just facts, but relationships, reasoning styles, and conceptual depth. You’ll work at the intersection of graph systems, LLM reasoning, and scalable AI infrastructure, bringing together symbolic structure and neural intelligence to redefine how knowledge lives digitally. What You’ll Do
Design and evolve the graph-based architecture that models a mind’s reasoning, associations, and conceptual hierarchies. Develop novel embeddings and contextual retrieval methods that make each mind distinct not just accurate, but alive. RAG & Context Innovation
Build next-generation retrieval-augmented generation systems that integrate structured graph reasoning with neural retrieval. Implement and refine LLM evaluation frameworks to ensure each mind improves over time in quality, consistency, and individuality. Applied AI & Performance
Push the performance of frontier LLMs through advanced prompt engineering, dynamic context shaping, and evaluation-driven iteration. Architect efficient, low-latency inference pipelines for thousands of simultaneous mind interactions. Systems & Product Integration
Bridge ML systems and product engineering shipping AI-powered features that shape user experience directly. Translate abstract research ideas into robust, scalable production systems powering thousands of live digital minds. Evals & Personalization
Define success metrics for “mind quality” advancing tone, style transfer, and reasoning fidelity. Build systems that continuously refine a digital mind’s authenticity and expressiveness. What You Bring
Core Expertise
4-6+ years of experience in AI or ML engineering, with at least 12 years hands-on with LLMs in production. Proven track record of building and deploying ML-powered systems that directly impact end-user experience. Strong Python expertise, including asynchronous programming, event loop optimization, and performance tuning. Experience with retrieval-augmented generation (RAG), context engineering, and LLM eval frameworks. Deep practical understanding of how LLMs reason, how to structure inputs, and how to measure improvement. Preferred / Bonus
Experience with graph databases or graph-based retrieval (Neo4j, ArangoDB, or custom-built graph layers). Background in document understanding, embeddings, or multimodal context assembly. Familiarity with AWS, distributed systems, and scalable backend architecture. Hands-on experience fine-tuning LLMs or building adapters for tone/style adaptation. You are a great fit if
You thrive on hard problems and are motivated by impact over title. You’re comfortable building at the intersection of research, product, and systems engineering. You have an engineer’s rigor, a creator’s imagination, and a philosopher’s curiosity. Benefits
Unlimited Learning Stipend: books, courses, or conferences of your choice. Comprehensive Health, Dental, and Vision coverage. 401(k) via Human Interest. Relocation assistance to San Francisco (if applicable). A creative, high-agency culture that celebrates curiosity and deep thinking.
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Catalyst Labs is a leading talent agency with a specialized vertical in Applied AI, Machine Learning, and Data Science. We stand out as an agency that’s deeply embedded in our clients’ recruitment operations. We partner directly with AI-first startups building products powered by LLMs, generative AI, intelligent automations; established tech companies scaling their ML infrastructure, recommendation systems, and data platforms; and enterprise innovation teams integrating AI into traditional domains such as finance, healthcare, and logistics. Our Client
Is reimagining how knowledge is shared. They’re building a new medium for human connection: interactive digital minds that people can talk to, learn from, and be guided by. The internet gave us static profiles and infinite feeds; they create something profoundly different: living, interactive identities that carry your voice, judgment, and worldview into every conversation. People don’t just read about you, they experience how you think. Their mission is bold and generational in scope: Make human wisdom abundant, personalized, and discoverable. Preserve legacies, unlock opportunity, and scale brilliance across generations. Trusted by thousands of the world’s most brilliant thinkers from Simon Sinek to Arnold Schwarzenegger and have tripled revenue, users, and mind interactions in the past six months, all organically. Backed by Sequoia Capital, Founders Fund, Lux Capital, and visionary angels including Michael Ovitz, Gokul Rajaram, and Olivia Wilde, they’re now scaling rapidly toward the next frontier of AI-driven human expression. Location
Jackson Square, San Francisco Work type
Fully on-site, 5 days a week Compensation
Above-market base + equity + benefits Visa
Sponsorship available only for candidates already in the United States The Role
As an Applied AI Engineer, you’ll help architect the foundation of next-generation Mind Architecture, the system that powers how digital minds learn, reason, and express individuality. Unlike traditional RAG systems that treat data as a static collection of documents, we build rich, hierarchical knowledge graphs that mirror how real experts think capturing not just facts, but relationships, reasoning styles, and conceptual depth. You’ll work at the intersection of graph systems, LLM reasoning, and scalable AI infrastructure, bringing together symbolic structure and neural intelligence to redefine how knowledge lives digitally. What You’ll Do
Design and evolve the graph-based architecture that models a mind’s reasoning, associations, and conceptual hierarchies. Develop novel embeddings and contextual retrieval methods that make each mind distinct not just accurate, but alive. RAG & Context Innovation
Build next-generation retrieval-augmented generation systems that integrate structured graph reasoning with neural retrieval. Implement and refine LLM evaluation frameworks to ensure each mind improves over time in quality, consistency, and individuality. Applied AI & Performance
Push the performance of frontier LLMs through advanced prompt engineering, dynamic context shaping, and evaluation-driven iteration. Architect efficient, low-latency inference pipelines for thousands of simultaneous mind interactions. Systems & Product Integration
Bridge ML systems and product engineering shipping AI-powered features that shape user experience directly. Translate abstract research ideas into robust, scalable production systems powering thousands of live digital minds. Evals & Personalization
Define success metrics for “mind quality” advancing tone, style transfer, and reasoning fidelity. Build systems that continuously refine a digital mind’s authenticity and expressiveness. What You Bring
Core Expertise
4-6+ years of experience in AI or ML engineering, with at least 12 years hands-on with LLMs in production. Proven track record of building and deploying ML-powered systems that directly impact end-user experience. Strong Python expertise, including asynchronous programming, event loop optimization, and performance tuning. Experience with retrieval-augmented generation (RAG), context engineering, and LLM eval frameworks. Deep practical understanding of how LLMs reason, how to structure inputs, and how to measure improvement. Preferred / Bonus
Experience with graph databases or graph-based retrieval (Neo4j, ArangoDB, or custom-built graph layers). Background in document understanding, embeddings, or multimodal context assembly. Familiarity with AWS, distributed systems, and scalable backend architecture. Hands-on experience fine-tuning LLMs or building adapters for tone/style adaptation. You are a great fit if
You thrive on hard problems and are motivated by impact over title. You’re comfortable building at the intersection of research, product, and systems engineering. You have an engineer’s rigor, a creator’s imagination, and a philosopher’s curiosity. Benefits
Unlimited Learning Stipend: books, courses, or conferences of your choice. Comprehensive Health, Dental, and Vision coverage. 401(k) via Human Interest. Relocation assistance to San Francisco (if applicable). A creative, high-agency culture that celebrates curiosity and deep thinking.
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