Remote-First Applied AI/ML Engineer for 3D Workflows

Intangible Technology Inc.; San Francisco, Northern (CA, KY); Hybrid; USD 140,000 - 190,000; Full time

Benefits offered by this job

Health insurance

401(k) plan

Flexible PTO

Job summary

Intangible Technology Inc. is seeking an Applied AI/Machine Learning Engineer to design and build assistive AI for interactive 3D workflows. You will collaborate with product and engineering teams to create agentic AI features that empower creators to visualize ideas and share them efficiently.

Preference for SF/Bay Area, CA, with remote candidates in North America and Western Europe. Strong background in ML, knowledge graphs, vector databases, and scalable backends is preferred.

Qualifications

• Experience building AI copilots.
• Experience building recommendation systems.
• Cloud ops, containerization, IaC and multi-tenant experience.
• Background in computational linguistics or knowledge representation.

Responsibilities

• Design and develop assistive AI technology for interactive, 3D workflows.
• Integrate cloud and client LLMs to drive creative workflows.
• Build and operate MCP servers at scale.
• Prototype and apply AI features in collaboration with product and engineering teams.
• Fine-tune or augment foundation models for domain-specific tasks.

Skills

Software development

ML fundamentals

Agentic AI frameworks

Vector databases

Graph databases

Python

ML libraries

End-to-end delivery

Education

Background in computational linguistics or knowledge representation

Tools

Neo4j

RDF

Property graphs

Job description

Intangible Technology Inc. is seeking an Applied AI/Machine Learning Engineer to design and build assistive AI for interactive 3D workflows. You will collaborate with product and engineering teams to create agentic AI features that empower creators to visualize ideas and share them efficiently.

Preference for SF/Bay Area, CA, with remote candidates in North America and Western Europe. Strong background in ML, knowledge graphs, vector databases, and scalable backends is preferred.