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Senior AI Research Scientist (Generative AI)

Nexus Future Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
17 Mei 2026
Deadline
17 Mei 2027

Job Description

We are on a mission to redefine the boundaries of artificial intelligence, targeting the transformative breakthroughs of 2026. Nexus Future Labs is seeking a visionary Senior AI Research Scientist to lead our cutting-edge R&D division. You will be at the forefront of developing next-generation Large Language Models (LLMs) and generative AI architectures that will power the digital ecosystem of tomorrow.

Why Join Us?

  • Work on high-impact projects that define the future of tech.
  • Competitive compensation package with equity options.
  • Access to state-of-the-art computing infrastructure and research grants.
  • A culture of innovation, diversity, and continuous learning.

Responsibilities

  • Lead Research Initiatives: Spearhead the design and implementation of novel generative AI models, focusing on scalability and efficiency for 2026 deployment.
  • Model Optimization: Engineer and fine-tune Transformer-based architectures to achieve state-of-the-art performance in NLP tasks.
  • Publish and Patent: Author high-impact research papers and secure patents for proprietary AI algorithms.
  • Collaborate Across Disciplines: Partner with software engineers and product managers to translate theoretical research into scalable production applications.
  • Mentorship: Guide junior researchers and data scientists, fostering a culture of technical excellence and innovation.

Qualifications

  • Education: PhD or Master's degree in Computer Science, Mathematics, or a related field with a focus on Machine Learning/AI.
  • Experience: 5+ years of professional experience in AI research, deep learning, or NLP.
  • Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX. Strong understanding of Transformer architectures, attention mechanisms, and diffusion models.
  • Research Acumen: Proven track record of publishing in top-tier conferences (NeurIPS, ICML, ACL) or having applied research deployed at scale.
  • Problem Solving: Ability to tackle complex, unstructured problems with creative algorithmic solutions.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning NLP Natural Language Processing Generative AI Large Language Models Transformer Research PhD Data Science

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