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Semantic Jobs (NOW HIRING)

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Semantic information

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$55.5K

$118.7K

$173.5K

How much do semantic jobs pay per year?

As of Jul 5, 2026, the average yearly pay for semantic in the United States is $118,674.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,500.00 and $133,500.00 per year, depending on experience, location, and employer.

What are semantic jobs?

Semantic jobs typically refer to roles that involve working with the meaning, structure, and interpretation of language or data. These positions are common in fields like linguistics, natural language processing (NLP), artificial intelligence, and information retrieval. Semantic professionals may develop algorithms to understand human language, create ontologies, or improve search engine relevance. Their work helps computers better interpret and process information as humans do, making technologies smarter and more intuitive.

What is a Semantic job?

A Semantic job typically involves working with meaning and context in language, data, or technology. It may include roles in natural language processing (NLP), knowledge representation, search engine optimization (SEO), or semantic web technologies. Professionals in this field develop algorithms, ontologies, and models to improve understanding and classification of information. These jobs are common in AI, data science, and digital marketing industries.

Which 3 jobs will survive AI?

Jobs that require complex human interaction, creativity, and critical thinking, such as healthcare professionals, educators, and skilled tradespeople, are less likely to be fully replaced by AI. These roles often involve emotional intelligence, hands-on skills, and adaptability that AI cannot replicate easily.

What is the difference between Semantic vs Data Analyst?

AspectSemanticData Analyst
Required CredentialsBackground in linguistics, computer science, or related fields; knowledge of semantic web technologiesDegree in statistics, mathematics, or related fields; proficiency in data analysis tools
Work EnvironmentResearch-focused, often in tech or AI companies, working on language understandingBusiness or research settings, analyzing data to inform decisions
Industry UsageUsed in AI, NLP, and semantic web projectsUsed across finance, marketing, healthcare, and other sectors
Common Search/ComparisonSemantic vs Data Analyst

Semantic professionals focus on understanding and structuring meaning in language and data, often working with AI and NLP technologies. Data Analysts interpret data sets to generate insights for business decisions. While both roles involve data, Semantic roles emphasize language and knowledge representation, whereas Data Analysts focus on statistical analysis and reporting.

What jobs pay 4000 a week without a degree?

Roles such as sales managers, real estate brokers, commercial pilots, and certain skilled trades like electricians or plumbers can pay around $4,000 weekly without requiring a college degree. These jobs often rely on experience, certifications, or licenses, and may involve commission, tips, or project-based pay structures.

What are the key challenges faced by Semantic Engineers when implementing knowledge graphs in large organizations?

Semantic Engineers often encounter challenges related to integrating disparate data sources, ensuring data quality, and aligning ontologies across departments. In large organizations, there can be legacy systems and inconsistent data formats, making it difficult to create a unified semantic model. Additionally, Semantic Engineers must collaborate closely with data architects, subject matter experts, and software developers to ensure the knowledge graph accurately reflects the organization's information needs and remains scalable as requirements evolve.

What kind of jobs in media bring in 150,000 a year?

High-paying media jobs that can earn $150,000 or more annually include senior roles such as media directors, executive producers, and digital strategists, often requiring extensive experience, leadership skills, and advanced knowledge of industry tools. These positions typically involve managing large teams, overseeing major projects, or developing strategic content, and may require advanced degrees or certifications in media, communications, or related fields.

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

To thrive as a Semantic Analyst, you need expertise in linguistics, natural language processing (NLP), data analysis, and a relevant degree such as linguistics, computer science, or information science. Familiarity with tools like Python, NLP libraries (e.g., NLTK, spaCy), and semantic annotation systems is typically required. Strong analytical thinking, attention to detail, and effective communication skills help you interpret complex language data and collaborate with technical teams. These competencies are vital to accurately extract, structure, and apply meaning from language data, driving insights and solutions in various industries.

Is ML a high paying job?

Machine learning (ML) roles are generally well-paid due to the specialized skills required, such as programming, data analysis, and knowledge of algorithms. Salaries vary based on experience, location, and industry, but many ML positions offer competitive compensation compared to other tech roles.
More about Semantic jobs
What cities are hiring for Semantic jobs? Cities with the most Semantic job openings:
What are the most commonly searched types of Semantic jobs? The most popular types of Semantic jobs are:
What states have the most Semantic jobs? States with the most job openings for Semantic jobs include:
What job categories do people searching Semantic jobs look for? The top searched job categories for Semantic jobs are:
Infographic showing various Semantic job openings in the United States as of June 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 33% In-person, and 67% Remote job distribution, with an average salary of $118,674 per year, or $57.1 per hour.
Semantic Solutions Architect (Remote)

Semantic Solutions Architect (Remote)

TopQuadrant

Raleigh, NC โ€ข On-site, Remote

Full-time

Posted 25 days ago


Job description

Our growing professional services team is looking for highly motivated full stack architects / developers/ consultants familiar with semantic technologies. Candidates should have experience or strong interest in working with Knowledge Graph technologies. The ideal candidate should excel at discerning the essence of complex problems and be creative in formulating solutions that use or extend the capabilities of our product and technology stack. Working for TopQuadrant brings you the opportunity to use cutting edge approaches ranging from semantic Knowledge Graphs systems (RDF, SHACL) to JavaScript/React, GraphQL, and other programming (Scala/Python/Java).


Semantic Solutions Architects work on customer projects that use our flagship product TopBraid Enterprise Data Governance (EDG) and the Linked Data standards it is based on to implement information management solutions. The role requires a person with strong skills for analyzing customer requirements and defining the appropriate solution design that considers all the required configurations and customizations of TopBraid EDG. Assisting customers with implementation activities is also a required skill.


The right candidate is a self-starter and quick learner interested in working with Knowledge Graph technologies to solve customer information management problems. Strong communication and interpersonal skills are required for close collaboration with customers, with our product development team located in Raleigh and with other TQ colleagues who are distributed across the US and Europe. Occasional travel will be required to customers throughout North America and Europe. However, most of the work will be performed remotely from TQ offices or a home office.


What youโ€™ll be doing:

  • Working with customers and other TQ consultants to understand requirements, assess them against product capabilities; and design approaches for configuring product capabilities to fully meet customer requirements.
  • Utilizing GraphQL, SPARQL and scripting technologies for developing services, data transformations and rules.ย 
  • Testing performance of data models, queries and algorithms.
  • Documenting deliverables and educate customers on their use of TopBraid EDG through product trainings and workshops, knowledge transfer and mentoring

What weโ€™re looking for:

Required Technical Skills and Qualifications

  • 3+ years software development experience, with skills in software engineering practices including version control using GitHub
  • Working knowledge of: HTML, CSS, JSON, JavaScript as a programming language
  • Understand template-driven application development to work with our semantic platform
  • Experience integrating full stack solutions with other enterprise infrastructure componentsย 

Communication Skills and Work Habits

  • Strong interpersonal skills and customer presence
  • Ability to work well independently as part of a distributed team
  • Excellent communication skills, both oral and written
  • Excellent analytical and problem-solving skills
  • Ability to effectively prioritize and execute tasks in a fast-paced environment
  • Creativity in dealing with loosely defined requirements
  • Willingness to travel occasionally

Bonus:

  • Experience in developing semantic models using SHACL or RDFS/OWL/SPARQL to address customer requirements
  • Practical understanding and experience implementing data governance/information management solutions
  • Experience with Java and/or Scala
  • Experience with GraphQL
  • Experience using JS libraries such as React, jQuery and Bootstrap
  • Experience using machine learning technologies
  • Experience with RDBMS such as Oracle or MySQL
  • Previous work with rules and rule-based system
  • Experience conducting training sessions
Working at TopQuadrant is best exemplified by our values:

  • Possibility (aka the โ€œWhy Notโ€ mentality):ย We embrace new ideas and ways of thinking because we never let an opportunity to โ€œlevel upโ€ pass us by. Piloting and testing good ideas will keep us learning. In general, moving faster is better.
  • Humility (aka โ€œGate check your baggageโ€):ย Best ideas win. We check our assumptions and our egos at the door. Titles, the โ€œthe way things were,โ€ or โ€œshould have beenโ€ just donโ€™t matter. The best ideas focus on the greater good. When in doubt, customers (and customer value) knows best.
  • Ownership:ย Finish lines matter. We expect ourselves and each other to step up and own processes and outcomes to completion. We give credit, let decision makers decide, ask for and give feedback, point fingers inward first, examine every cost, and never make excuses because thatโ€™s what makes great teams great.
  • Partnership:ย Customers value us because we provide them with superpowers theyโ€™ve never had. We do not simply provide a product or service, we engage as equal partners in their solution. We influence the outcome and express our expertise and opinions unapologetically. And when we succeed, we share in the value we deliver because we value our time, our technology, and ourselves.
  • Teamwork:ย ย Be the person youโ€™d want to work with. Build each other up.