Catalyst Labs
About Catalyst Labs
Catalyst Labs is a leading talent agency specialized in Applied AI, Machine Learning, and Data Science. We embed in our clients’ recruitment operations and partner directly with AI‑first startups, established tech companies scaling ML infrastructure, and enterprise innovation teams integrating AI into finance, healthcare, and logistics.
Client We collaborate with founders, CTOs, and heads of AI driving applied intelligence from model optimization to productized AI workflows.
Job Overview Location:
San Francisco, Jackson Square Work type:
Fully on‑site, 5 days a week Compensation:
Above‑market base + equity + benefits Visa:
Sponsorship available for candidates already in the United States
Role: Applied AI Engineer Architect the foundation of next‑generation Mind Architecture powering digital minds to learn, reason, and express individuality.
What You’ll Do
Knowledge Graph & Mind Architecture
– Design and evolve the graph‑based architecture modeling a mind’s reasoning, associations, and conceptual hierarchies. Develop novel embeddings and contextual retrieval methods that make each mind distinct 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 continuously improve mind quality.
Applied AI & Performance
– Push 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. 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 AI/ML engineering experience, 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 evaluation 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.
#J-18808-Ljbffr
Client We collaborate with founders, CTOs, and heads of AI driving applied intelligence from model optimization to productized AI workflows.
Job Overview Location:
San Francisco, Jackson Square Work type:
Fully on‑site, 5 days a week Compensation:
Above‑market base + equity + benefits Visa:
Sponsorship available for candidates already in the United States
Role: Applied AI Engineer Architect the foundation of next‑generation Mind Architecture powering digital minds to learn, reason, and express individuality.
What You’ll Do
Knowledge Graph & Mind Architecture
– Design and evolve the graph‑based architecture modeling a mind’s reasoning, associations, and conceptual hierarchies. Develop novel embeddings and contextual retrieval methods that make each mind distinct 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 continuously improve mind quality.
Applied AI & Performance
– Push 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. 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 AI/ML engineering experience, 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 evaluation 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.
#J-18808-Ljbffr