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Senior AI Research Scientist - AGI & Generative Models

FutureScale Technologies
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
Live Update
20 Mei 2026
Deadline
20 Mei 2027

Job Description

We are pioneering the next evolution of intelligence. As a Senior AI Research Scientist at FutureScale Technologies, you will play a pivotal role in architecting the foundational models that will define the landscape of technology in 2026 and beyond. Join a world-class team of engineers, ethicists, and researchers dedicated to building Artificial General Intelligence (AGI) that enhances human creativity and problem-solving.

We offer a competitive benefits package, fully remote-first flexibility, and the opportunity to publish groundbreaking research in top-tier conferences.

Responsibilities

  • Lead R&D Initiatives: Spearhead the development of next-generation generative models and autonomous agents, pushing the boundaries of Large Language Models (LLMs) and multimodal AI.
  • Model Architecture: Design, train, and optimize deep neural networks for complex reasoning tasks, ensuring scalability and efficiency.
  • Research Publication: Author high-impact research papers and contribute to open-source communities, establishing FutureScale as a thought leader in the AI ecosystem.
  • Cross-Functional Collaboration: Partner with product engineering teams to translate theoretical research into practical, deployable applications.
  • Technical Mentorship: Mentor junior researchers and data scientists, fostering a culture of innovation and continuous learning.
  • Ethical AI Implementation: Ensure all models adhere to strict ethical guidelines, bias mitigation protocols, and safety standards.

Qualifications

  • Education: PhD or Master’s degree in Computer Science, Mathematics, Statistics, or a related technical field.
  • Experience: 5+ years of professional experience in machine learning, deep learning, or artificial intelligence research.
  • Technical Skills: Expert proficiency in Python, PyTorch, or TensorFlow. Strong understanding of distributed training frameworks and GPU optimization.
  • Mathematical Foundation: Deep knowledge of linear algebra, calculus, probability, and optimization theory.
  • Project History: Proven track record of publishing in prestigious venues (NeurIPS, ICML, ICLR) or shipping industry-defining AI products.
  • Communication: Excellent written and verbal communication skills, capable of explaining complex technical concepts to diverse audiences.

Required Skills

Python PyTorch TensorFlow Deep Learning Machine Learning NLP LLMs Research PhD AI AGI Distributed Systems GPU Optimization

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