Deandre Jerkins

Deandre Jerkins

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Artificial Intelligence Researcher | MLOps Engineer at ElevenLabs
Tennessee, United States

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Résumé

Jobs verified_user 0% verified
  • Avaamo
    Artificial Intelligence Researcher | MLOps Engineer
    Avaamo
    Aug 2023 - Mar 2025 (1 year 8 months)
    • Optimized a GPT2-style Text-to-Speech (TTS) model, achieving a 10x reduction in response time for real-time conversational AI applications. • Trained a diffusion-based TTS model by implementing parallel data loading and distributed computing, achieving optimized training completion time. • Trained a large-scale speech synthesis model using pretrained feature encoders, resulting in high-quality audio generation with enhanced speech clarity and fluency. • Deployed the TTS model to Fly.io, optimizing for dynamic resource allocation using Redis, and reduced deployment costs by 50% while maintaining model performance at scale. • Built and maintained a FastAPI-based inference endpoint for seamless integration of AI models, creating a Docker con
  • ElevenLabs
    Artificial Intelligence Engineer | Lead NLP Engineer
    ElevenLabs
    Apr 2018 - Jul 2023 (5 years 4 months)
    • Led the development of state-of-the-art NLP models, improving language understanding and generation capabilities, achieving a 15% improvement in model accuracy. • Redesigned architecture for AI-driven chatbots, integrating function calls and SQL queries, resulting in a 40% reduction in response times and enhanced scalability. • Finetuned Llama and integrated it with CLIP model using Reinforcement Learning from Human Feedback (RLHF), creating a multimodal chatbot capable of processing both text and image inputs. • Collaborated with cross-functional teams to integrate AI models into production, driving a 30% reduction in operational costs and improving system efficiency. • Developed a context-aware NLP system that boosted customer engagemen
  • Numenta
    Artificial Intelligence Intern
    Numenta
    Mar 2016 - Apr 2018 (2 years 2 months)
    • Analyzed 5+ network models and identified 3 critical errors in architectures, improving model robustness and performance. • Contributed to the development of object tracking systems using YOLO, reducing memory usage by 50% and improving real-time object detection efficiency. • Implemented anomaly detection frameworks using temporal memory patterns, improving the detection of irregularities in video streams by 40%, enhancing predictive maintenance systems. • Enhanced classification model accuracy by 20% through advanced visual data preprocessing, enabling better insights in industrial automation and quality control systems. • Supported AI research by leveraging tools like NumPy, SciPy, and Scikit-learn to develop simple neural networks and
Education verified_user 0% verified
  • T
    Master's degree, Computer Science
    The Open University of Japan
    Apr 2012 - Apr 2018 (6 years 1 month)