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Lead Research Engineer in Multi-Modal AI

2 months ago

California, United States Moonhub Full time

Company Overview: Moonhub is a dynamic start-up focused on revolutionizing the Healthtech sector through innovative AI solutions.

Position Overview: We are seeking a visionary Founding Research Engineer specializing in multi-modal AI, particularly in vision-language models and video comprehension. The ideal candidate will possess a robust background in cutting-edge transformer architectures, with a strong emphasis on pre-training and fine-tuning on extensive datasets. Experience in constructing foundational AI models is highly advantageous.

Key Responsibilities:

  • Research Leadership: Spearhead groundbreaking research initiatives in multi-modal AI, focusing on vision-language integration and advanced video analysis techniques.
  • Model Innovation: Drive the development of transformer models, emphasizing their pre-training and fine-tuning on large-scale datasets.
  • Foundation Model Development: Create adaptable foundational AI models that can be utilized across various applications within our platform.
  • Data Optimization: Enhance the utilization of large datasets for training purposes to ensure the development of robust, scalable, and efficient models.
  • Collaborative Engagement: Collaborate closely with cross-functional teams, including data scientists, radiologists, and product managers, to align research efforts with business goals.
  • Thought Leadership: Contribute to the broader AI community through publications, patents, and presentations at leading conferences.
  • Continuous Learning: Stay abreast of the latest trends in AI and integrate innovative research findings into ongoing projects.

Qualifications:

  • Experience: Minimum of 5 years in AI research, with a focus on language or vision models, and at least 1 year dedicated to vision-language integration or video analysis.
  • Expertise: In-depth knowledge of transformer models, with practical experience in pre-training and fine-tuning large-scale models.
  • Specialization: Strong proficiency in video comprehension, video question answering, and visual question answering.
  • Foundation Model Experience: Proven track record in developing foundational models is highly desirable.
  • Technical Proficiency: Strong skills in Python and familiarity with deep learning frameworks such as PyTorch or TensorFlow.
  • Research Acumen: A solid history of high-quality research, evidenced by publications in prestigious conferences or journals.
  • Analytical Skills: Exceptional problem-solving abilities, with a knack for creatively tackling complex research challenges.
  • Communication Skills: Excellent verbal and written communication skills, capable of articulating complex concepts to diverse audiences.