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Remote Knowledge Engineer Jobs in California (NOW HIRING)

Astrix Inc

AWS Cloud Engineer (Remote)

San Francisco, CA · On-site +1

$40 - $45/hr

Position: AWS Cloud Engineer - Python (Contract) Location: Remote (U.S.) Duration: 12-Month ... Knowledge of data structures, API/schema design, and distributed systems. Preferred: * Experience ...

PM2CM

Cost Engineer Hybrid-Remote

San Bernardino, CA · On-site +1

Hybrid-Remote (Tuesday and Wednesday in the office/field) JOB OPPORTUNITY: WE ARE HIRING JUNIOR ... Good working knowledge of MS Office Software Suite Requirements Minimum Qualification: A ...

PM2CM

Cost Engineer Hybrid-Remote

Riverside, CA · On-site +1

Hybrid-Remote (Tuesday and Wednesday in the office/field) JOB OPPORTUNITY: WE ARE HIRING JUNIOR ... Good working knowledge of MS Office Software Suite Requirements Minimum Qualification: A ...

PM2CM

Cost Engineer Hybrid-Remote

Pomona, CA · On-site +1

Hybrid-Remote (Tuesday and Wednesday in the office/field) JOB OPPORTUNITY: WE ARE HIRING JUNIOR ... Good working knowledge of MS Office Software Suite Requirements Minimum Qualification: A ...

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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.

Manufacturing Design Engineer - Remote

Palo Alto, CA • Remote

YO AI Labs
See more jobs at YO AI Labsexternal

$40 - $100/hr

Full-time

Posted 17 days ago

Job description

Manufacturing Design Engineer

Job Type: Contractor
Location: Remote

Job Overview

We are seeking experienced Manufacturing Design Engineers to contribute to an advanced mechanical design and manufacturing project. In this role, you will apply your engineering expertise to help improve next-generation AI systems through high-quality, real-world design input.

You will use FreeCAD or similar parametric CAD platforms to create, document, review, and validate production-ready mechanical components and assemblies. This opportunity is ideal for professionals with strong mechanical design, manufacturing, CAD validation, and technical documentation experience.

No prior AI experience is required—your engineering expertise and domain knowledge are what matter most.

Scope of Work

  1. Create and modify detailed parametric 3D CAD models of mechanical components and assemblies using FreeCAD or comparable CAD software.

  2. Develop comprehensive engineering drawings, including GD&T, dimensional requirements, and tolerance stack-ups, suitable for manufacturing handoff.

  3. Design components for manufacturing processes including CNC machining, sheet metal fabrication, plastics, and injection molding.

  4. Perform CAD validation and quality assurance reviews to verify model accuracy, design intent, and production readiness.

  5. Prepare clear technical documentation, design notes, and assembly instructions for use as high-quality reference materials.

  6. Review and incorporate feedback from technical reviewers to improve CAD models, drawings, and supporting documentation.

  7. Apply Design for Manufacturing (DFM) principles to ensure designs are practical, efficient, and manufacturable.

  8. Identify and resolve modeling, dimensional, assembly, and manufacturability issues before production handoff.

Required Skills

  • FreeCAD

  • Parametric CAD Modeling

  • Mechanical Design

  • 3D CAD Modeling

  • Assembly Design

  • Engineering Drawings

  • CAD Validation & Quality Assurance

  • Technical Documentation

  • Design for Manufacturing (DFM)

  • GD&T and tolerance analysis

  • Manufacturing design principles

Preferred Qualifications

  1. 2+ years of experience designing mechanical components for manufacturing environments.

  2. Strong proficiency in FreeCAD or similar parametric CAD software, including advanced modeling, assemblies, and drawing generation.

  3. Hands-on experience with manufacturing considerations for CNC machining, sheet metal, plastics, and injection molding.

  4. Strong understanding of GD&T, tolerance analysis, and DFM best practices.

  5. Demonstrated ability to create production-grade CAD models and validate designs against real-world manufacturability requirements.

  6. Experience interpreting engineering drawings, manufacturing specifications, and technical documentation.

  7. Strong attention to detail and ability to identify CAD and documentation inconsistencies.

  8. Excellent written and verbal communication skills for documenting technical decisions and collaborating with reviewers.

  9. Ability to work independently in a remote environment and meet project quality and delivery requirements