
Physics Subject Matter Expert
4 semanas atrás
Overview
Job Title: Physics Subject Matter Expert – AI Training & Content Development
About Innodata:
Innodata (NASDAQ: INOD) is a global leader in data engineering and AI-powered solutions, working with 4 of the top 5 global technology companies and over 2,000 enterprise clients worldwide. Operating in 13 global locations with a workforce of 5,000+ subject matter experts, Innodata leads innovation in machine learning (ML), natural language processing (NLP), and large language model (LLM) training.
By combining cutting-edge AI technology, deep domain expertise, and secure infrastructure, Innodata delivers transformative solutions that power the next generation of intelligent systems.
About the Role:
We are seeking a Physics Subject Matter Expert (SME) with exceptional analytical, problem-solving, and writing skills to join our AI / LLM training team. You will play a crucial role in developing, curating, and evaluating advanced physics content to enhance AI models’ reasoning, accuracy, and ability to explain complex physics concepts. This role is ideal for physicists, researchers, and academics passionate about science communication and AI innovation.
Responsibilities- Content Development : Create high-quality physics datasets, including: conceptual explanations of physics principles (classical, quantum, and modern physics); problem sets and numerical solutions; detailed derivations of equations and laws; technical summaries and scientific research briefs. Build domain-specific datasets across physics subfields such as: Mechanics, Thermodynamics, and Electromagnetism; Quantum Mechanics, Particle Physics, and Nuclear Physics; Astrophysics, Relativity, and Cosmology; Materials Science and Condensed Matter Physics; Computational Physics and Applied Physics.
- Model Evaluation & AI Training : Evaluate LLM-generated physics content for accuracy, clarity, rigor, and logical reasoning. Detect and correct conceptual gaps, numerical errors, and inconsistencies in AI outputs. Help define data quality standards and evaluation rubrics for scientific reasoning.
- Collaboration & R&D : Work closely with AI engineers, computational linguists, and data scientists to improve AI reasoning. Provide domain expertise for designing AI benchmarks and test scenarios. Contribute to research on physics education, simulation modeling, and AI-assisted scientific research.
- Master’s or PhD in Physics, Applied Physics, Engineering Physics, or a related discipline (PhD preferred).
- Strong foundation in theoretical and applied physics.
- Demonstrated expertise in one or more areas: computational modeling, simulations, or numerical methods; advanced topics (e.g., quantum field theory, condensed matter, astrophysics).
- Proven experience in academic publishing, science communication, or curriculum design.
- Strong technical writing skills and ability to explain complex concepts clearly.
- Familiarity with AI / ML models, data annotation, and prompt engineering (bonus).
- Experience in LaTeX, Python, or scientific computing tools.
- Knowledge of AI fairness and bias detection in STEM datasets.
- Shape the future of AI by embedding physics expertise into large-scale models.
- Collaborate with top-tier researchers and engineers globally.
- Influence next-gen AI capabilities in scientific reasoning.
- Work remotely with flexibility and innovation-driven teams.
- Candidates must complete an English Language Assessment.
- Mandatory and non-billable step.
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