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Senior AI Research Scientist (Generative AI) - 2026 Vision

Nexus Horizon Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
30 Juni 2026
Deadline
30 Jun 2027

Job Description

We are seeking a visionary Senior AI Research Scientist to join our elite R&D division. At Nexus Horizon Labs, we aren't just building software; we are architecting the intelligence layer of the digital world for the year 2026 and beyond. You will be at the forefront of the AI revolution, pushing the boundaries of what is possible with Large Language Models (LLMs) and autonomous agents.

Why Join Us?
We offer a competitive salary, equity package, and the opportunity to work on projects that will define the future of human-machine interaction. Our team is composed of world-class engineers and researchers dedicated to solving the hardest problems in artificial general intelligence.

Responsibilities

  • Lead Research Initiatives: Spearhead the design and implementation of cutting-edge Generative AI architectures, focusing on scalability and efficiency.
  • Model Optimization: Fine-tune and optimize large-scale transformer models to improve inference speed and reduce computational costs.
  • Paper Publication: Publish high-impact research papers in top-tier conferences (NeurIPS, ICML, ACL) to establish thought leadership in the AI community.
  • Technical Mentorship: Mentor junior researchers and data scientists, fostering a culture of innovation and continuous learning within the team.
  • Product Integration: Collaborate closely with engineering and product teams to translate theoretical research into robust, deployable AI products.

Qualifications

  • Education: PhD or Master’s degree in Computer Science, Machine Learning, or a related quantitative field.
  • Experience: 5+ years of experience in deep learning, NLP, or reinforcement learning, with a strong portfolio of published work.
  • Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and familiarity with Hugging Face Transformers.
  • Language Model Expertise: Deep understanding of LLM training pipelines, alignment techniques, and RAG (Retrieval-Augmented Generation).
  • Problem Solving: Demonstrated ability to tackle complex mathematical and algorithmic challenges with innovative solutions.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning NLP Large Language Models AI Research RAG Natural Language Processing

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