Senior Research Scientist

Who We Are Pindrop is the Real Human + Right Human® Identity Trust Platform for the AI era. As AI-driven fraud and deepfakes erode trust in digital communication, Pindrop delivers continuous identity verification and deepfake detection across voice, video, and digital interactions in real time. Enterprises rely on Pindrop to secure billions of high-risk customer interactions each year, including top U.S. banks, as well as leading insurers and healthcare providers. Powered by models trained on more than 1.5 billion real-world interactions annually and protected by 300+ patents, Pindrop restores trust while reducing fraud, lowering operational costs, and improving customer experience. Recognized by TIME as one of the Top 10 Most Influential Software Companies of 2026 and by Inc. for Best in Business for Innovation, Pindrop is backed by leading investors including Andreessen Horowitz, IVP, and CapitalG. What you’ll do As a Senior Research Scientist on the Video team, you will be responsible for advancing core research initiatives and translating advanced computer vision and deepfake detection models into real-world, scalable enterprise solutions. In this role, you will: Drive forward-looking research that advances Pindrop’s core technologies in audio-visual deepfake detection, synthetic media identification, and real-time video processing. Design, implement, and evaluate novel machine learning and computer vision algorithms tailored for video data and meeting analytics. Partner closely with engineering teams to transition complex research prototypes and tools into efficient, production-ready systems across multiple platforms. Maintain high standards for model reproducibility, publish patents, and author peer-reviewed papers for top-tier computer vision, machine learning, and speech conferences. Act as a technical authority by conducting code and research reviews, mentoring junior researchers, and utilizing empirical data to influence product strategy. Who you are You are energized by open-ended, ambiguous research problems. You maintain high focus and scientific rigor even when experiments fail, quickly incorporating negative findings to improve model strategy. You seamlessly bridge the gap between research and engineering teams. You can explain complex AI/ML and computer vision concepts with absolute clarity to both technical and non-technical stakeholders. You take complete ownership of your research projects from initial hypothesis to final evaluation. You excel at balancing long-term scientific exploration with near-term, tangible business outcomes. You operate with absolute technical integrity. You proactively document assumptions, risks, and experimental limitations while consistently delivering on your promises. You design and evaluate machine learning architectures with a sharp awareness of bias, drift, and operational deployment constraints, balancing rapid innovation with responsible AI principles. Your skill-set Must-Haves: PhD in Computer Science, Artificial Intelligence, Engineering, Mathematics, or a related quantitative field (or equivalent industry experience). 3+ years of professional research experience in Deep Learning, specifically focused on Computer Vision, image/video deepfake detection, facial recognition, or generative AI. Deep technical expertise in real-time video processing, video data acquisition, pipeline preparation, and model deployment across cloud or edge environments. Strong programming proficiency in Python, alongside hands-on mastery of modern machine learning frameworks such as PyTorch, TensorFlow, or Keras. A proven track record of successful project delivery and publication of peer-reviewed research or patents at prestigious scientific conferences. Nice-to-Haves: Strong programming skills in C/C++ or experience working with deployment tools like Go, TF-Lite, and TF-Micro. Experience competing in or leveraging benchmarks from prominent Computer Vision and machine learning challenges (e.g., N