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AI Research Scientist - Future Tech (2026 Focus) | San Francisco, CA

Nexus Horizon Labs
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
Live Update
15 Mei 2026
Deadline
15 Mei 2027

Job Description

We are pioneering the next generation of Artificial General Intelligence and are seeking a visionary AI Research Scientist to lead our 2026 roadmap. If you are passionate about pushing the boundaries of machine learning and shaping the future of technology, we want to meet you.

At Nexus Horizon Labs, we don't just predict the future; we build it. Our team is dedicated to developing scalable, safe, and ethical AI systems that will define the technological landscape of 2026 and beyond. Join us in this high-impact role where your work will directly influence the trajectory of human-computer interaction.

Responsibilities

  • Lead Research: Drive the conceptualization and execution of cutting-edge research projects focused on Long-Term Context AI and multimodal systems.
  • Model Development: Architect, train, and optimize large-scale neural network models to achieve state-of-the-art performance benchmarks.
  • Collaboration: Work closely with cross-functional engineering teams to translate theoretical research into scalable, production-ready software.
  • Publication: Author high-impact academic papers and patents to establish thought leadership in the AI community.
  • Mentorship: Mentor junior researchers and data scientists, fostering a culture of innovation and continuous learning.
  • Ethical AI: Ensure all models adhere to strict ethical guidelines and safety protocols regarding bias and deployment.

Qualifications

  • Education: PhD in Computer Science, Machine Learning, or a related quantitative field.
  • Experience: Minimum of 5 years of experience in research or applied machine learning roles.
  • Technical Skills: Proficiency in Python, PyTorch, or TensorFlow with a deep understanding of deep learning architectures.
  • Specialization: Strong background in Natural Language Processing (NLP), Reinforcement Learning, or Computer Vision.
  • Tools: Experience with distributed computing frameworks (e.g., Ray, Kubernetes) and MLOps pipelines.
  • Communication: Excellent written and verbal communication skills, with the ability to present complex technical concepts to diverse audiences.

Required Skills

Artificial Intelligence Machine Learning NLP Python PyTorch TensorFlow Deep Learning Research AGI Reinforcement Learning

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