Catalyst Labs
About Us
Catalyst Labs is a leading talent agency with a specialized vertical in Applied AI, Machine Learning, and Data Science. 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. We collaborate directly with founders, CTOs, and Heads of AI in those themes who are driving the next wave of applied intelligence from model optimization to productized AI workflows. We take pride in facilitating conversations that align with your technical expertise, creative problem-solving mindset, and long-term growth trajectory in the evolving world of intelligent systems. 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
Knowledge Graph & Mind Architecture
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.
Other roles in Applied AI / ML in the US, check them out here: Applied AI / ML engineer focusing on LLMs, and Document processing: [https://www.careers-page.com/catalyst-labs]
#J-18808-Ljbffr
Catalyst Labs is a leading talent agency with a specialized vertical in Applied AI, Machine Learning, and Data Science. 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. We collaborate directly with founders, CTOs, and Heads of AI in those themes who are driving the next wave of applied intelligence from model optimization to productized AI workflows. We take pride in facilitating conversations that align with your technical expertise, creative problem-solving mindset, and long-term growth trajectory in the evolving world of intelligent systems. 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
Knowledge Graph & Mind Architecture
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.
Other roles in Applied AI / ML in the US, check them out here: Applied AI / ML engineer focusing on LLMs, and Document processing: [https://www.careers-page.com/catalyst-labs]
#J-18808-Ljbffr