Demo

Machine Learning Researcher – Probabilistic Models & AI Reasoning

Axiomatic AI
Cambridge, MA Full Time
POSTED ON 1/17/2025
AVAILABLE BEFORE 4/16/2025

Axiomatic_AI"s mission :

Axiomatic_AI aims to accelerate R&D by "Automated Interpretable Reasoning" (AIR) a verifiably truthful AI model built for reasoning in science and engineering. Axiomatic_AI is hiring top talent interested in a future of human reasoning aided by not replaced by AI, and a future that empowers a new generation of innovators to solve important problems through deep-tech engineering in the semiconductor ecosystem.

Responsibilities :

  • Project 1 : Probabilistic Models for Uncertainty Quantification in AI
  • Develop advanced probabilistic models to quantify uncertainty in AI predictions.
  • Integrate these models with existing AI systems to improve reliability and decision-making.
  • Validate the effectiveness of the models through real-world applications and case studies.
  • Project 2 : Integrating Factor Networks and Knowledge Graphs for Enhanced AI Reasoning
  • Design methods to integrate factor networks and knowledge graphs to represent complex relationships.
  • Implement these integrated models to enhance AI reasoning and inference capabilities.
  • Evaluate and validate these models in real-world domains through case studies and applications.

Key Requirements :

  • Educational Background : A Ph.D. (or relevant experience) in Machine Learning, Artificial Intelligence, Data Science, or a related field.
  • Technical Skills : Strong expertise in probabilistic modeling, statistics, and machine learning. Proficiency with probabilistic graphical models, factor networks, and knowledge graphs.
  • Experience : Hands-on experience developing and applying AI models, including knowledge graph-based systems.
  • Familiarity with relevant tools and libraries such as Bayesian Deep Learning and the Knowledge Graph Toolkit.
  • Proven ability to apply research in practical, real-world AI systems.
  • Preferred Qualifications :

  • Demonstrated experience with uncertainty quantification techniques in AI systems.
  • Prior research experience or publications in AI reasoning, probabilistic modeling, and knowledge graphs.
  • Ability to work independently and in a collaborative team environment to solve complex technical problems.
  • Benefits :

  • Opportunity to work on groundbreaking AI research projects with real-world impact.
  • Collaboration with an experienced, innovative team in a forward-thinking organization.
  • Flexible working environment.
  • If you are passionate about pushing the boundaries of AI and machine learning, particularly in probabilistic modeling and AI reasoning, we encourage you to apply!

    How to Apply : Please submit your resume, a brief cover letter detailing your relevant experience, and links to any relevant publications or GitHub repositories.

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