Catalyst Labs
Applied AI Engineer
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Catalyst Labs
About Catalyst Labs
Catalyst Labs is a leading talent agency focused on Applied AI, Machine Learning and Data Science. We work closely with AI‑first startups, established technology companies and enterprise innovation teams to embed AI into product and infrastructure at scale.
Client Overview
Our flagship client reimagines knowledge sharing through digital minds – living, interactive identities that learn, reason and express individuality. They are building a platform that turns static profiles into dynamic, conversational experiences for millions of users.
Location & Work
Jackson Square, San Francisco
Fully on‑site, 5 days a week
Above‑market base + equity + benefits
Visa sponsorship only for candidates already in the United States
The Role
As an
Applied AI Engineer , you will architect the foundation of next‑generation Mind Architecture – a system that integrates graph reasoning, LLMs and scalable AI infrastructure to power digital minds.
Responsibilities
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 lively.
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 continuous improvement in quality, consistency and individuality.
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 to ship AI‑powered features that shape user experience directly.
Translate 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 with 12+ years hands‑on with LLMs in production.
Proven track record building and deploying ML‑powered systems that directly impact end‑user experience.
Strong Python expertise – asynchronous programming, event loop optimization and performance tuning.
Experience with RAG, context engineering and LLM evaluation frameworks.
Deep practical understanding of LLM reasoning, input structuring and measuring improvement.
Preferred / Bonus
Experience with graph databases or graph‑based retrieval (Neo4j, ArangoDB, custom 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
Referrals increase your chances of interviewing at Catalyst Labs by 2x
#J-18808-Ljbffr
–
Catalyst Labs
About Catalyst Labs
Catalyst Labs is a leading talent agency focused on Applied AI, Machine Learning and Data Science. We work closely with AI‑first startups, established technology companies and enterprise innovation teams to embed AI into product and infrastructure at scale.
Client Overview
Our flagship client reimagines knowledge sharing through digital minds – living, interactive identities that learn, reason and express individuality. They are building a platform that turns static profiles into dynamic, conversational experiences for millions of users.
Location & Work
Jackson Square, San Francisco
Fully on‑site, 5 days a week
Above‑market base + equity + benefits
Visa sponsorship only for candidates already in the United States
The Role
As an
Applied AI Engineer , you will architect the foundation of next‑generation Mind Architecture – a system that integrates graph reasoning, LLMs and scalable AI infrastructure to power digital minds.
Responsibilities
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 lively.
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 continuous improvement in quality, consistency and individuality.
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 to ship AI‑powered features that shape user experience directly.
Translate 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 with 12+ years hands‑on with LLMs in production.
Proven track record building and deploying ML‑powered systems that directly impact end‑user experience.
Strong Python expertise – asynchronous programming, event loop optimization and performance tuning.
Experience with RAG, context engineering and LLM evaluation frameworks.
Deep practical understanding of LLM reasoning, input structuring and measuring improvement.
Preferred / Bonus
Experience with graph databases or graph‑based retrieval (Neo4j, ArangoDB, custom 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
Referrals increase your chances of interviewing at Catalyst Labs by 2x
#J-18808-Ljbffr