STEM Expert (US & International)

Reposted 3 Days Ago
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Hiring Remotely in USA
Remote
110-110 Hourly
Expert/Leader
Software
The Role
The role involves evaluating and annotating scientific content to enhance AI model performance in scientific reasoning and problem-solving across STEM disciplines.
Summary Generated by Built In

The future of AI — whether in training or evaluation, classical ML or agentic workflows — starts with high-quality data.

At HumanSignal, we’re building the platform that powers the creation, curation, and evaluation of that data. From fine-tuning foundation models to validating agent behaviors in production, our tools are used by leading AI teams to ensure models are grounded in real-world signal, not noise.

Our open-source product, Label Studio, has become the de facto standard for labeling and evaluating data across modalities — from text and images to time series and agents-in-environments. With over 250,000 users and hundreds of millions of labeled samples, it’s the most widely adopted OSS solution for teams working on building AI systems. 

Label Studio Enterprise builds on that traction with the security, collaboration, and scalability features needed to support mission-critical AI pipelines — powering everything from model training datasets to eval test sets to continuous feedback loops.We started before foundation models were mainstream, and we’re doubling down now that AI is eating the world. If you're excited to help leading AI teams build smarter, more accurate systems — we’d love to talk.

STEM Expert - Scientific Content Review & Evaluation SpecialistAbout the Role

HumanSignal is seeking highly qualified STEM (Science, Technology, Engineering, Mathematics) experts to contribute to cutting-edge AI development projects. This role involves evaluating, annotating, and validating scientific and technical content across multiple STEM disciplines to improve AI model performance in scientific reasoning, problem-solving, and explanation.

Compensation

Up to $110 USD/hour based on qualifications and project complexity

Required QualificationsEducation
  • Master's degree required in a STEM-related field
  • PhD strongly preferred in:
    • Physics
    • Chemistry
    • Biology
    • Engineering (any discipline)
    • Earth Sciences
    • Materials Science
    • Astronomy/Astrophysics
    • Or closely related scientific disciplines
Degree Field Requirements

Candidates must hold degrees directly in STEM fields. Acceptable programs include:

  • Physics (Theoretical, Experimental, Applied)
  • Chemistry (Organic, Inorganic, Physical, Analytical)
  • Biology (Molecular, Cellular, Ecology, Genetics)
  • Engineering (Mechanical, Electrical, Chemical, Civil, etc.)
  • Materials Science
  • Earth Sciences/Geology
  • Astronomy/Astrophysics
  • Biochemistry/Biophysics
  • Environmental Science
Responsibilities
  • Review and evaluate scientific content for accuracy, rigor, and clarity
  • Annotate scientific reasoning steps and experimental methodologies
  • Validate AI-generated scientific explanations across various complexity levels
  • Identify errors in scientific concepts, calculations, and experimental design
  • Provide detailed feedback on scientific writing and problem-solving approaches
  • Work with problems spanning introductory to advanced STEM topics
  • Assess the appropriateness of scientific analogies and explanations
Qualifications
  • Deep understanding of scientific principles across one or more STEM domains
  • Strong analytical and critical thinking skills
  • Excellent attention to detail and scientific precision
  • Ability to clearly articulate complex scientific concepts
  • Experience with scientific notation, units, and dimensional analysis
  • Familiarity with experimental design and data analysis
  • Knowledge of scientific literature and research methodologies
  • Ability to work independently and meet deadlines
Work Details
  • Flexible, project-based work - work on your own schedule
  • Remote position - work from anywhere
  • Variable hours based on project availability and your capacity
  • Ongoing training and calibration provided
  • Quality-focused environment with performance feedback
Ideal Candidate Profile
  • Active researchers, professors, industry scientists, or recent graduates in STEM fields
  • Strong publication record or demonstrated scientific expertise
  • Experience in scientific research, teaching, or industry applications
  • Ability to work across multiple STEM disciplines
  • Passion for advancing AI capabilities in scientific domains
How to Apply

Interested candidates should be prepared to:

  1. Submit CV/resume highlighting STEM qualifications
  2. Provide proof of advanced degree(s)
  3. Complete a brief STEM content assessment
  4. Participate in a qualification review

HumanSignal is a leading provider of AI data annotation and labeling services, powering the development of next-generation AI systems. We work with top technology companies and research institutions to create high-quality training data.

HumanSignal is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Top Skills

AI
Label Studio
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The Company
HQ: San Francisco, California
51 Employees
Year Founded: 2019

What We Do

HumanSignal (formerly known as Heartex) enables data science teams to build AI models with their company DNA. With the emergence of generative AI, it’s more important than ever to build highly differentiated models by guiding foundation models with proprietary data and human feedback. Creators of Label Studio, the most popular open source data labeling platform, HumanSignal enables data scientists to develop high quality datasets and workflows for model training, fine tuning and continuous validation. Today, the Label Studio open source community has more than 250,000 users who have collectively annotated more than 100 million pieces of data. Label Studio Enterprise is available as a cloud service with enhanced security, automation, quality review workflows, and performance reporting, used by leading data science teams including Bombora, Geberit, Outreach, Wyze, and Zendesk.

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