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Knowledge Engineering Jobs in California (NOW HIRING)

Mentor and guide engineers on the team while helping raise the technical bar across the ... Knowledge of web security principles and best practices. * Strong problem-solving and analytical ...

Java or Scala 5+ years experience with big data platforms Familiarity with ML/AI workflows and feature engineering to support analytics, reporting, and machine learning use cases Knowledge ...

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Knowledge Engineering information

What does a knowledge engineer do?

A knowledge engineer designs, develops, and maintains systems that capture and organize knowledge for artificial intelligence and expert systems. They analyze information, create ontologies, and use tools like knowledge bases and reasoning algorithms to enable machines to simulate human decision-making. Strong skills in logic, data modeling, and programming are essential for this role.

What is knowledge engineering?

Knowledge engineering is a field within artificial intelligence that focuses on creating systems capable of simulating human decision-making and reasoning. It involves gathering, organizing, and structuring information so that computers can use it to solve complex problems. Knowledge engineers work to build knowledge bases and rule-based systems, often collaborating with domain experts to codify expertise into a form that machines can process. This discipline is fundamental in the development of expert systems, intelligent agents, and modern AI applications.

What engineers make $500,000 a year?

Highly experienced engineers in specialized fields such as software engineering, data engineering, or systems architecture can earn $500,000 or more annually, especially in senior or executive roles at large technology companies. These positions often require advanced skills, certifications, and extensive industry experience, and may include bonuses and stock options that contribute to total compensation.

What is the difference between Knowledge Engineering vs Data Scientist?

AspectKnowledge EngineeringData Scientist
Required CredentialsTypically degrees in computer science, AI, or related fields; certifications in knowledge systemsDegrees in statistics, computer science, or mathematics; certifications in data analysis or machine learning
Work EnvironmentDeveloping knowledge bases, expert systems, and AI applications in tech or research settingsAnalyzing data, building predictive models, and deriving insights in various industries
Employer & Industry UsageUsed in AI development, research institutions, and tech companiesUsed across finance, healthcare, marketing, and tech sectors

While both roles involve working with data and AI, Knowledge Engineers focus on creating structured knowledge bases and expert systems, whereas Data Scientists analyze data to extract insights and build predictive models. Understanding these differences helps in choosing the right career path or job focus.

How does a Knowledge Engineer typically collaborate with subject matter experts during a project?

Knowledge Engineers frequently work closely with subject matter experts (SMEs) to extract, structure, and formalize domain knowledge into usable formats for AI systems or knowledge bases. This collaboration often involves conducting interviews, facilitating workshops, and reviewing documentation to ensure complex concepts are accurately captured. Effective communication and iterative feedback are key, as Knowledge Engineers must bridge the gap between technical requirements and expert insights. This teamwork helps ensure that the resulting system is both technically sound and aligned with real-world practices.

What engineers make 200,000 a year?

Senior knowledge engineers, especially those with expertise in artificial intelligence, machine learning, and data science, can earn $200,000 or more annually. High salaries are often associated with extensive experience, advanced certifications, and working in industries like technology, finance, or consulting, typically in roles involving complex problem-solving and specialized tools.

How much does a knowledge engineer make?

A knowledge engineer's salary typically ranges from $70,000 to $130,000 annually, depending on experience, education, and location. Senior roles or those with specialized skills in AI, machine learning, or data management can earn higher salaries. Many positions require proficiency with knowledge representation, ontologies, and tools like Protégé or OWL.

What are the key skills and qualifications needed to thrive as a Knowledge Engineer, and why are they important?

To thrive as a Knowledge Engineer, you need a strong background in computer science, logic, and data modeling, often supported by a relevant degree. Familiarity with knowledge representation systems, ontologies, semantic web technologies, and tools like Protégé is typically required, along with experience in programming languages such as Python or Java. Strong analytical thinking, problem-solving abilities, and clear communication skills help you collaborate with subject matter experts and translate complex information into structured formats. These skills are critical for building effective knowledge-based systems that drive intelligent decision-making and organizational efficiency.
What are popular job titles related to Knowledge Engineering jobs in California? For Knowledge Engineering jobs in California, the most frequently searched job titles are:
What job categories do people searching Knowledge Engineering jobs in California look for? The top searched job categories for Knowledge Engineering jobs in California are:
What cities in California are hiring for Knowledge Engineering jobs? Cities in California with the most Knowledge Engineering job openings:
Director, Warehouse Engineering and Delivery

Director, Warehouse Engineering and Delivery

EMPIRE

Ontario, CA • On-site

$141K - $194K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

This job post has expired today. Applications are no longer accepted.


Job description

At Prologis, we don't just lead the industry-we define it with a 1.3 billion square foot portfolio and an annual throughput of approximately $3.2 trillion. We create the intelligent infrastructure that powers global commerce, seamlessly connecting the digital and physical worlds. From agile supply chains to energy solutions, our ecosystems help your business move faster, operate smarter and grow sustainably. With unmatched scale, innovation and expertise, Prologis is a category of one-not just shaping the future of logistics but building what comes next.

Job Title:

Director, Warehouse Engineering and Delivery

Company:

Prologis

Prologis Operations Essentials is redefining how technical, infrastructure, and systems solutions support large enterprise customers. We combine deep domain knowledge, engineering capability, and commercial discipline to deliver practical, execution-ready solutions across warehouse design, automation, racking, electrical systems, and integrated delivery.

As a Director, Warehouse Engineering and Delivery, you will serve as the senior technical and delivery lead for complex warehouse consulting engagements. Reporting into the Director of Warehouse Design and Innovation, this role is focused on how consulting is delivered across projects.

This role is designed for a senior engineering leader with 8-10+ years of experience in warehouse consulting delivery, bringing deep technical judgment and hands-on execution leadership to complex engagements. The role is delivery-first, hands-on, and project-centric.

Key Responsibilities

  • Lead end-to-end delivery of complex warehouse consulting engagements from post-sale handoff through final recommendation, accountable for scope, quality, schedule, and outcomes.
  • Serve as the senior technical and project delivery lead, translating client business challenges into structured engineering analyses and execution-ready solution options.
  • Direct and coordinate cross-functional delivery teams composed of internal engineering resources and external partners or subcontractors, ensuring alignment, accountability, and performance across all contributors.
  • Develop warehouse layouts, process flows, capacity models, labor productivity analyses, and automation concepts grounded in operational feasibility and facility constraints.
  • Apply strong Industrial Engineering rigor through throughput modeling, scenario analysis, capacity planning, and financial impact evaluation using advanced Excel and data visualization tools such as Tableau.
  • Provide ad hoc technical review of Statements of Work and scope assumptions to ensure delivery feasibility and execution clarity.
  • Lead client working sessions and milestone reviews while proactively managing risks, assumptions, dependencies, and stakeholder alignment.
  • Ensure consulting recommendations are practical, defensible, data-driven, and aligned with commercial and implementation realities.
  • Develop and refine standardized templates, analytical models, and repeatable delivery methodologies to improve consistency, speed, and quality across engagements.

Required:

  • Bachelor's degree in industrial engineering or related engineering discipline.
  • 8-10+ years of experience in solution engineering, Industrial Engineering, supply chain consulting, or similar roles.
  • Proven track record leading complex, client-facing engineering consulting engagements.
  • Strong project leadership skills with clear scope, quality, and time discipline.
  • Deep warehouse domain expertise including layout design, material handling systems, and automation concepts.
  • Advanced proficiency in Excel for modeling, scenario analysis, and quantitative evaluation.
  • Demonstrated ability to translate ambiguous business problems and operational data into structured quantitative analyses and actionable engineering recommendations.
  • Demonstrated proficiency in AutoCAD to produce accurate, execution-ready warehouse layouts and design concepts.
  • Exposure to automation technologies including AS/RS, G2P systems, AMRs, and conveyance.
  • Strong communication skills across technical and executive stakeholders.

Preferred:

  • Experience using FlexSim or similar simulation tools for operational modeling and validation.
  • Experience developing standardized templates, dashboards, and repeatable delivery methodologies.
  • Advanced degree preferred.
  • Experience using Tableau or similar tools for operational data visualization and analysis.

Hiring Salary Range of: $141,600 - $194,700. Salary and whole compensation package (bonus target & LTI) to be determined by the candidate's location, education, experience, knowledge, skills, and abilities, as well as internal equity and alignment with market data.

People First

Each of us working at Prologis plays an essential role in the enduring success of our company. We value people who are decisive, courageous and adaptable. While we are one company, locations and departments operate with autonomy and accountability. Individuals take the initiative here.

When you join Prologis, you work shoulder to shoulder with some of the top talent in the industry to do the best work of your career. Every employee belongs. Every employee contributes. Employees advance their careers here.

As a successful global enterprise, Prologis has never lost sight of what matters most, our strong belief that our people are the most important part of our business. And because of that, we provide a generous total rewards package and take a lot of time to focus on quality management and leadership development. People come first here.

All full-time roles in the US come with a robust benefits package which includes healthcare, dental, and vision insurance for employees and eligible dependents. Prologis also offers several other wellness, financial, and work/lifestyle-specific benefits. Our 401(k) retirement plan has a company match of 50% up to 12% of eligible compensation. We also offer generous PTO with a starting accrual of 22 days a year in addition to paid holidays and volunteer time.

All job offers are contingent upon successful completion of background verification. Prologis is an Equal Opportunity/Affirmative Action employer and all qualified applicants will receive consideration for employment without regard to race, color, religions, sex, national origin, sexual orientation, gender identity, disability status, protected veteran status, or any other characteristic protected by law.

Employment Type:

Full time

Location:

Chicago, Illinois

Additional Locations:

Atlanta, Georgia, Dallas, Texas, Inland Empire-Ontario Office