Catalyst Labs
Company Overview
Catalyst Labs is a leading talent agency specializing in Applied AI, Machine Learning, and Data Science. We partner directly with AI‑first startups, established tech companies, and enterprise innovation teams to embed AI expertise into recruitment operations. Client
Interactive Digital Minds
is reimagining how knowledge is shared. They build a medium for human connection:
living, interactive identities
that carry your voice, judgment, and worldview into every conversation. Their mission is bold and generational:
make human wisdom abundant, personalized, and discoverable. Role
As an
Applied AI Engineer , you will architect the foundation of next‑generation Mind Architecture that powers how digital minds learn, reason, and express individuality. You will work at the intersection of graph systems, LLM reasoning, and scalable AI infrastructure, combining symbolic structure and neural intelligence. Responsibilities
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. 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. 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. 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. 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. Qualifications
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 evaluation frameworks. Deep practical understanding of how LLMs reason, how to structure inputs, and how to measure improvement. Preferred Skills
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. Fit
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, on‑site, 5 days a week Visa
Sponsorship available only for candidates already in the United States
#J-18808-Ljbffr
Catalyst Labs is a leading talent agency specializing in Applied AI, Machine Learning, and Data Science. We partner directly with AI‑first startups, established tech companies, and enterprise innovation teams to embed AI expertise into recruitment operations. Client
Interactive Digital Minds
is reimagining how knowledge is shared. They build a medium for human connection:
living, interactive identities
that carry your voice, judgment, and worldview into every conversation. Their mission is bold and generational:
make human wisdom abundant, personalized, and discoverable. Role
As an
Applied AI Engineer , you will architect the foundation of next‑generation Mind Architecture that powers how digital minds learn, reason, and express individuality. You will work at the intersection of graph systems, LLM reasoning, and scalable AI infrastructure, combining symbolic structure and neural intelligence. Responsibilities
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. 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. 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. 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. 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. Qualifications
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 evaluation frameworks. Deep practical understanding of how LLMs reason, how to structure inputs, and how to measure improvement. Preferred Skills
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. Fit
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, on‑site, 5 days a week Visa
Sponsorship available only for candidates already in the United States
#J-18808-Ljbffr