Catalyst Labs · 3 months ago
Applied AI Engineer
Austin, TX
Full-time
Onsite
Mid, Senior Level
4+ years expCatalyst Labs is a leading talent agency specializing in Applied AI, Machine Learning, and Data Science. The Applied AI Engineer will architect the foundation of next-generation Mind Architecture, focusing on building hierarchical knowledge graphs and advanced retrieval systems to enhance digital minds' reasoning and individuality.
Management Consulting
No H1B
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 not just accurate, but 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
Qualification
Required
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
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
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.
Company
Catalyst Labs
Welcome to Catalyst Labs – Powering Catalytic Growth At Catalyst Labs, catalytic growth isn't just a concept, it's our driving force.
11-50 employees
Funding
Current Stage
Early StageCompany data provided by crunchbase