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Marcus James Thompson

Marcus James Thompson

Marcus James Thompson – Senior Machine Learning Engineer at Google AI Research, specializing in scalable machine learning models and recommendation algorithms. Holds an MSc in Machine Learning from MIT and has prior experience at Facebook AI Research and Tesla, focusing on AI-driven advancements in user personalization and autonomous systems.

marcusthompson@investortip.com

Education

  • University: Stanford University, School of Engineering Years Attended: 2012–2016 Degree: Bachelor of Science (BSc) in Computer Science, focused on Machine Learning and AI
  • Advanced Degree: Master of Science (MSc) in Machine Learning from MIT (2017–2019)

Additional Training and Certifications:

  • Advanced Course: "Deep Learning Specialization" on Coursera (2020)
  • Certification: Google Certified Professional Machine Learning Engineer (2021)
  • Certification: AWS Certified Machine Learning – Specialty (2022)

Languages

  • English: Native
  • French: Fluent

Career History

Tesla, Inc. Career History Machine Learning Engineer Intern Years 2016–2018

Developed ML models for Tesla’s autonomous driving technology.

Facebook AI Research (FAIR) Career History Machine Learning Research Scientist Years 2019–2021

Enhanced recommendation systems and content personalization.

Google AI Research Career History Senior Machine Learning Engineer Years 2022-2023

Leads development of scalable ML models for search enhancement and user experience. Conducts research in AI, focusing on recommendation systems and data automation. Oversees a team creating machine learning solutions for Google Cloud AI.

Professional Skills

  • Machine Learning: Expertise in neural networks and large-scale data analysis.
  • Data Processing: Proficient in managing vast datasets for ML models.
  • AI Solutions for Search: Developed algorithms improving search engagement.
  • Cloud Computing: Experienced in AI solutions using Google Cloud and AWS.
  • Programming Languages: Python (Expert) JavaScript, C++, SQL (Intermediate).

Personal Qualities

  • Innovative thinking, problem-solving, strong leadership, and adaptability.

Publications

  • Research Paper: "Neural Networks for Personalized Search" (AI Research Journal, 2022)
  • Study: "AI-Powered Recommendations" (Journal of Machine Learning, 2021)
  • Publication: "Autonomous Vehicles and ML" (Tesla AI Research, 2019)

Professional Activities

  • Speaker: NeurIPS Conference (2023)
  • Panelist: CVPR Conference (2022)
  • Keynote: AI and Machine Learning Summit (2021)

Awards and Memberships

  • Award: "Best AI Research Paper," Google AI (2022)
  • Membership: AAAI
  • Recognition: "Top 30 Under 30 in AI" (2021)

Interests and Hobbies

  • Exploring AI advancements
  • Integrating AI in gaming
  • Fitness activities such as soccer and running.
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