Catalyst Labs
About Catalyst Labs
Catalyst Labs is a leading talent agency focused on Applied AI, ML, and Data Science.
The Role As an Applied AI Engineer you’ll help architect the foundation of next‑generation Mind Architecture that powers how digital minds learn, reason, and express individuality.
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, accurate, and 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 improve mind quality over time.
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 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.
Location Jackson Square, San Francisco
Employment type Full‑time
Compensation Above‑market base + equity + benefits
Visa Sponsorship available only for candidates already in the United States
#J-18808-Ljbffr
The Role As an Applied AI Engineer you’ll help architect the foundation of next‑generation Mind Architecture that powers how digital minds learn, reason, and express individuality.
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, accurate, and 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 improve mind quality over time.
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 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.
Location Jackson Square, San Francisco
Employment type Full‑time
Compensation Above‑market base + equity + benefits
Visa Sponsorship available only for candidates already in the United States
#J-18808-Ljbffr