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Applied AI Researcher

Role overview

Summary

This role focuses on investigating methods for detecting synthetic media and digital fraud within a research and engineering team at a digital trust and security company. You will translate effective research into production software, contributing to advancements in media forensics and fraud prevention.

Qualifications

  • At least 3 years of experience training deep learning models in PyTorch.
  • An MS or PhD in computer science, electrical engineering, or a related field, or equivalent research experience.
  • Strong machine learning foundations and experience building, training, and evaluating models.
  • Computer vision knowledge, including CNNs and vision transformers.
  • Preferred: Experience in at least one relevant area: synthetic media detection, image or video forensics, or generative models.

Responsibilities

  • Investigate AI methods for synthetic media detection and fraud prevention.
  • Design experiments, establish baselines, and evaluate models on realistic data.
  • Implement research ideas and collaborate with engineering to bring successful approaches into production.
  • Document methods and findings, and contribute to technical writing.

Key facts

Hard skills

Other skills

  • Communication

About the company

Clera Inc. logo

Clera Inc.

  • Job Boards & Talent Marketplaces
  • 11–50
Clera is an AI talent agent that represents job candidates and connects them directly with hiring managers at venture-backed startups. The platform uses artificial intelligence to match professionals with suitable career opportunities and facilitates introductions via email, iMessage, and WhatsApp, bypassing traditional job application processes.

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Job description

About the Role

Join a small research and engineering team at a digital trust and security company. You will investigate methods for detecting synthetic media and digital fraud, then help translate effective research into production software.

What You'll Do

  • Investigate AI methods for synthetic media detection, media forensics, and fraud prevention.

  • Read and reproduce research, then assess which approaches are worth pursuing.

  • Design experiments, establish baselines, and evaluate models on realistic data.

  • Implement research ideas and collaborate with engineering to bring successful approaches into production.

  • Analyze failure cases and improve model reliability, generalization, and computational efficiency.

  • Document methods and findings, contribute to technical writing, and prioritize research around practical needs.

What We're Looking For

  • At least 3 years of experience training deep learning models in PyTorch, including taking at least one model from concept to production.

  • An MS or PhD in computer science, electrical engineering, or a related field, or equivalent research experience.

  • Strong machine learning foundations and experience building, training, and evaluating models.

  • Computer vision knowledge, including CNNs and vision transformers, and the tradeoffs between them at small parameter counts.

  • Experience in at least one relevant area: synthetic media detection, image or video forensics, audio spoofing detection, generative models, or adversarial robustness.

  • Ability to critically assess research papers, design experiments, communicate findings clearly, and turn research into shipped software.

  • Evidence of research and engineering ability through production systems, publications, open-source work, or substantial applied projects.

Compensation & Benefits

Base salary is flexible based on experience and candidacy. The package includes a performance bonus and 0.25% to 1% equity. Visa sponsorship is available.

Location

On-site in New York, New York, United States.

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