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Symbolic Ai Jobs (NOW HIRING)

Mercor

Automated Planning PhD - AI Expert

New York, NY · Remote

$55 - $80/hr

Provide expert insights into automated planning and symbolic AI to inform future AI innovations . Qualifications Must-Have * PhD or advanced degree in Computer Science, Artificial Intelligence ...

Intuit

Senior Staff AI Research Scientist

San Diego, CA · On-site

$226K - $306K/yr

Conduct original research in decision-focused AI, probabilistic modeling, causal inference, simulation-based planning, agentic and multi-agent systems, neuro-symbolic AI, deep learning, and/or LLM ...

Intuit

Senior Staff AI Research Scientist

Mountain View, CA · On-site

$226K - $306K/yr

Conduct original research in decision-focused AI, probabilistic modeling, causal inference, simulation-based planning, agentic and multi-agent systems, neuro-symbolic AI, deep learning, and/or LLM ...

Intuit

Senior Staff AI Research Scientist

Mountain View, CA · On-site

$226K - $306K/yr

Conduct original research in decision-focused AI, probabilistic modeling, causal inference, simulation-based planning, agentic and multi-agent systems, neuro-symbolic AI, deep learning, and/or LLM ...

Intuit

Senior Staff AI Research Scientist

San Diego, CA · On-site

$226K - $306K/yr

Conduct original research in decision-focused AI, probabilistic modeling, causal inference, simulation-based planning, agentic and multi-agent systems, neuro-symbolic AI, deep learning, and/or LLM ...

Intuit

Senior Staff AI Research Scientist

Mountain View, CA · On-site

$226K - $306K/yr

Conduct original research in decision-focused AI, probabilistic modeling, causal inference, simulation-based planning, agentic and multi-agent systems, neuro-symbolic AI, deep learning, and/or LLM ...

o9 Solutions, Inc.

Senior AI Architect

Dallas, TX · On-site

$128K - $174K/yr

Turning VUCA into Value with Neuro-Symbolic AI. The north star for our customers is the APEX operating model-a state of integrated, autonomous, AI-driven planning that eliminates the friction between ...

o9 Solutions, Inc.

Senior AI Architect

$132K - $180K/yr

Turning VUCA into Value with Neuro-Symbolic AI. The north star for our customers is the APEX operating model-a state of integrated, autonomous, AI-driven planning that eliminates the friction between ...

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Symbolic Ai information

What is symbolic AI?

Symbolic AI is a branch of artificial intelligence that uses high-level, human-readable symbols and logic to represent knowledge and solve problems. It relies on rules, ontologies, and reasoning engines to mimic human decision-making and understanding. Unlike machine learning methods, which learn patterns from data, symbolic AI systems are programmed with explicit rules and relationships. This approach is particularly useful for tasks that require explainability and reasoning, such as expert systems and knowledge graphs.

What skills and qualifications are needed to thrive as a symbolic AI engineer?

To excel as a Symbolic AI Engineer, you need a solid background in computer science, logic, and mathematics, often supported by a degree in a related field. Experience with knowledge representation languages (like OWL or Prolog), logic programming, and relevant AI frameworks is highly valuable. Analytical thinking, problem-solving, and effective communication are crucial soft skills for designing and explaining complex reasoning systems. These skills ensure the development of robust, interpretable AI solutions that can tackle intricate, rule-based problems in various industries.

What are common challenges faced by professionals working in symbolic AI roles, and how can they be addressed?

Professionals in Symbolic AI roles often encounter challenges related to integrating symbolic reasoning with machine learning approaches, as well as handling the complexity of knowledge representation. Collaborating effectively with data scientists and software engineers is crucial, as is staying up-to-date with developments in hybrid AI systems. Regularly participating in interdisciplinary meetings and knowledge-sharing sessions can help address these challenges and enhance project outcomes.

What is the difference between Symbolic Ai vs Data Scientist?

AspectSymbolic AiData Scientist
Required CredentialsComputer Science, AI, or related degrees; knowledge of logic and knowledge representationStatistics, Mathematics, Computer Science; proficiency in programming and data analysis
Work EnvironmentResearch labs, AI development teams, academiaTech companies, finance, healthcare, consulting firms
Industry UsageKnowledge-based systems, expert systems, reasoning enginesData analysis, predictive modeling, machine learning applications

Symbolic AI focuses on rule-based reasoning and knowledge representation, often used in expert systems. Data Scientists analyze data to build models and extract insights. While both roles involve AI, Symbolic AI emphasizes logic and knowledge structures, whereas Data Scientists focus on data-driven modeling and statistical analysis.

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Symbolic Ai jobs near you
Infographic showing various Symbolic Ai job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 21% Part Time, and 3% Contract. Highlights an 64% Physical, 4% Hybrid, and 32% Remote job distribution.

NEURO-SYMBOLIC AI Researcher@ 100% Remote Role

Palnar

Remote

Full-time

Re-posted 20 days ago

Job description

Key Responsibilities:
  • Develop neuro-symbolic AI algorithms and methods for manufacturing applications.
  • Design, develop, implement, and evaluate novel neuro-symbolic AI algorithms using Bosch data.
  • Engage in technical discussions and idea generation to enhance existing research solutions.
  • Ensure clean, efficient, and well-documented implementations of neuro-symbolic AI methods.
  • Publish research findings at leading AI conferences to contribute to advancements in the field.
  • Help shape the future of AI-driven products and services.

Qualifications:
  • PhD in Computer Science, Engineering, or Data Science with at least 4 publications.
  • 6+ years of programming experience, particularly in Python.
  • 5+ years of experience with neuro-symbolic AI algorithms and toolkits (e.g., PyG, PyKEEN, PyTorch).
  • Strong theoretical and practical knowledge of neuro-symbolic AI principles.
  • Proven publication record in machine learning, knowledge graphs, or related fields.
  • Excellent communication skills.

Apply