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Nathan Knopf

@nathanknopf

Senior Machine Learning Engineer specializing in AI and NLP solutions.

United States
Message

What I'm looking for

I am looking for a role that challenges my skills in AI and machine learning, fosters innovation, and offers opportunities for professional growth.

I am a Senior Machine Learning Engineer with a strong background in developing advanced AI solutions, particularly in natural language processing and real-time translation systems. At Lingopal, I designed and deployed a real-time speech-to-speech translation pipeline, utilizing cutting-edge technologies like OpenAI Whisper and Tacotron 2. My work has significantly improved multilingual communication, enabling seamless interactions across diverse languages.

Previously, I served as a Machine Learning Engineer at John Deere, where I led predictive maintenance modeling and developed edge-optimized vision models for agricultural applications. My projects not only reduced equipment downtime but also enhanced crop health detection through innovative machine learning techniques. I am passionate about leveraging AI to solve real-world problems and continuously seek to improve model performance and deployment efficiency.

Experience

Work history, roles, and key accomplishments

LI
Current

Senior Machine Learning Engineer

Lingopal

Aug 2022 - Present (3 years 10 months)

Designed and deployed a real-time speech-to-speech translation pipeline using OpenAI Whisper, Tacotron 2, and custom voice cloning models. Developed and launched context-aware conversational AI using RAG architecture with LLaMA 2, Huggingface Transformers, and LangChain.

JD

Machine Learning Engineer II

John Deere

Aug 2020 - Jul 2022 (1 year 11 months)

Led predictive maintenance modeling for agricultural machinery using XGBoost and LSTM, reducing unexpected equipment downtime by 22%. Built edge-optimized vision models for crop health detection using TensorFlow Lite and OpenCV.

JD

Machine Learning Engineer I

John Deere

Oct 2017 - Jul 2020 (2 years 9 months)

Developed supervised learning models for equipment usage classification using Scikit-learn and Pandas. Constructed rule-based and ML-enhanced anomaly detection systems to flag abnormal behavior in transmission systems.

Education

Degrees, certifications, and relevant coursework

University of Utah logoUU

University of Utah

Master's Degree, Computer Science

Completed a Master's degree in Computer Science. Focused on advanced topics in the field, preparing for a career in machine learning and data science.

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