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Remote Knowledge Engineer Jobs in California (NOW HIRING)

YO AI Labs

AI Software Engineer - Remote

San Jose, CA · Remote

$80 - $120/hr

Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training ... Strong knowledge of performance optimization and tuning . * Excellent written and verbal ...

YO AI Labs

AI Software Engineer - Remote

Palo Alto, CA · Remote

$80 - $120/hr

Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training ... Strong knowledge of performance optimization and tuning . * Excellent written and verbal ...

YO AI Labs

AI/ML Engineer - Remote

San Jose, CA · Remote

$200 - $350/hr

Remote Job Summary We are seeking an experienced AI/ML Engineer to build and deploy secure ... Strong knowledge of cloud AI services, including AWS GovCloud, Google GovCloud, Azure IL5+, Vertex ...

YO AI Labs

AI/ML Engineer - Remote

Palo Alto, CA · Remote

$200 - $350/hr

Remote Job Summary We are seeking an experienced AI/ML Engineer to build and deploy secure ... Strong knowledge of cloud AI services, including AWS GovCloud, Google GovCloud, Azure IL5+, Vertex ...

YO AI Labs

AI Software Engineer - Remote

Los Angeles, CA · Remote

$80 - $120/hr

Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training ... Strong knowledge of performance optimization and tuning . * Excellent written and verbal ...

YO AI Labs

AI/ML Software Engineer - Remote

San Jose, CA · Remote

$80 - $120/hr

Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training ... Strong knowledge of performance optimization and tuning . * Excellent written and verbal ...

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Remote Knowledge Engineer information

What is a remote knowledge engineer?

A Remote Knowledge Engineer is a professional who designs, develops, and maintains systems that organize and manage knowledge, often using artificial intelligence and machine learning. They work from a remote location, leveraging digital tools to gather, structure, and analyze information for organizations. Their responsibilities may include building knowledge graphs, developing ontologies, and ensuring that data is accessible and usable for decision-making. Remote Knowledge Engineers collaborate with subject matter experts, software developers, and data scientists to optimize knowledge management solutions. They play a key role in helping organizations turn complex data into actionable insights, all while working outside of a traditional office environment.

What are the key skills and qualifications needed to thrive as a remote knowledge engineer?

To excel as a Remote Knowledge Engineer, you generally need expertise in knowledge management, ontologies, data modeling, and a relevant degree in computer science or information science. Familiarity with technical tools such as semantic web technologies (e.g., RDF, OWL), knowledge graph platforms, and query languages like SPARQL is often required. Strong analytical thinking, problem-solving, and effective communication are crucial soft skills for collaborating across distributed teams and translating complex information. These skills ensure the creation, organization, and optimization of knowledge systems that support informed decision-making and efficient remote operations.

How does a remote knowledge engineer typically collaborate with subject matter experts and development teams?

As a Remote Knowledge Engineer, you will frequently interact with subject matter experts (SMEs) to extract, structure, and validate knowledge for use in AI systems or knowledge bases. Collaboration is often conducted through virtual meetings, shared documentation, and project management tools. You’ll also work closely with developers to integrate structured knowledge into systems and ensure accuracy. Effective communication and the ability to translate complex concepts into structured data formats are key to success in this remote, cross-functional environment.

What is the difference between Remote Knowledge Engineer vs Remote Data Scientist?

AspectRemote Knowledge EngineerRemote Data Scientist
Required CredentialsBachelor's in CS, AI, or related field; knowledge of ontologies and knowledge basesBachelor's or higher in CS, Statistics, or related; proficiency in programming and statistical analysis
Work EnvironmentCollaborates with AI teams, develops knowledge systems, often in tech or AI companiesAnalyzes data, builds models, works in tech, finance, or healthcare sectors
Employer & Industry UsageUsed in AI, knowledge management, and enterprise solutionsCommon in data-driven industries like tech, finance, healthcare

While both roles involve technical expertise, Remote Knowledge Engineers focus on developing and managing knowledge bases and AI systems, whereas Remote Data Scientists analyze data to derive insights. Both roles often work in tech industries and require strong technical backgrounds, but their core responsibilities differ significantly.

What are the most commonly searched types of Knowledge Engineer jobs in California?

The most popular types of Knowledge Engineer jobs in California are:

What are popular job titles related to Remote Knowledge Engineer jobs in California?

For Remote Knowledge Engineer jobs in California, the most frequently searched job titles are:

What job categories do people searching Remote Knowledge Engineer jobs in California look for?

The top searched job categories for Remote Knowledge Engineer jobs in California are:

What cities in California are hiring for Remote Knowledge Engineer jobs?

Cities in California with the most Remote Knowledge Engineer job openings:

Remote Knowledge Engineer jobs near you
Infographic showing various Remote Knowledge Engineer job openings in California as of September 2026, with employment types broken down into 82% Full Time, and 18% Contract. Highlights an 27% In-person, and 73% Remote job distribution.

AI Software Engineer - Remote

San Jose, CA • Remote

YO AI Labs
See more jobs at YO AI Labsexternal

$80 - $120/hr

Full-time

Posted 14 days ago

Job description

Senior Software Engineer

Job Type: Contractor (~15 hours/week)
Location: Remote

Job Summary

We are seeking experienced Senior Software Engineers to support an AI training project by creating reinforcement learning environments that evaluate AI models on complex software engineering tasks using Model Context Protocol (MCP) tools.

You will design reproducible environments, deterministic verification, and reference solutions for tasks such as bug fixing, feature implementation, codebase refactoring, and performance optimization. No prior AI experience is required.

Key Responsibilities
  • Create reinforcement learning environments for software engineering tasks.
  • Design tasks involving bug fixing, feature development, refactoring, and performance optimization.
  • Build deterministic verification systems and golden reference solutions.
  • Evaluate AI agents' ability to reason through complex codebases and use MCP tools effectively.
  • Develop realistic, reproducible software engineering scenarios.
  • Ensure tasks accurately measure coding ability, problem-solving, and tool usage.
  • Document solutions and provide clear technical feedback.
Required Skills
  • Strong proficiency in Python 3, Java, Rust, C++, or TypeScript.
  • Strong understanding of algorithms and data structures.
  • Experience with bug fixing and debugging complex software issues.
  • Proven experience in feature implementation and codebase refactoring.
  • Strong knowledge of performance optimization and tuning.
  • Excellent written and verbal communication.
  • Strong attention to detail.
Preferred Qualifications
  • Experience working with large-scale or distributed codebases.
  • Familiarity with AI/ML systems is a plus but not required.
  • Experience with rigorous code reviews and software engineering best practices.
  • Experience working effectively in remote or cross-functional teams.
Hiring Process
  1. Submit an application and screening questions.
  2. Complete an AI interview (~30 minutes).
  3. Complete a technical assessment, if required.
  4. Hiring Manager review.
Compensation

Compensation is output-based, with payment provided per task that meets project specifications. Minimum weekly submission requirements may apply.

Availability

Selected experts should be prepared to begin their first tasks within 24–48 hours of completing onboarding.