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Information Technology 🏢 Full Time ⭐️ Verified

Senior AI Research Scientist (Generative Models)

Nexus Horizon
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
Live Update
28 Juni 2026
Deadline
28 Jun 2027

Job Description

Join the Visionaries of 2026.

Nexus Horizon is at the forefront of the next industrial revolution. We are looking for a world-class Senior AI Research Scientist to lead the development of our proprietary Generative AI architectures. If you are passionate about pushing the boundaries of Large Language Models (LLMs) and shaping the intelligence of tomorrow, this is your opportunity to define the future of technology.

We offer a competitive compensation package, equity options, and the chance to work on projects that will change the world. Come build the tools of the next decade with us.

Responsibilities

  • Lead R&D Initiatives: Spearhead the research and development of cutting-edge Generative AI models, focusing on scalability and efficiency for the 2026 landscape.
  • Model Optimization: Architect and optimize deep learning frameworks (PyTorch/TensorFlow) to reduce inference costs and improve model latency.
  • Publish & Patent: Drive the company’s intellectual property portfolio by publishing seminal research papers in top-tier conferences (NeurIPS, ICML, ICLR) and filing patents.
  • Technical Mentorship: Mentor junior data scientists and engineers, fostering a culture of innovation and rigorous scientific inquiry.
  • Collaboration: Work closely with product engineering teams to translate theoretical research into deployable, production-grade AI solutions.
  • Data Strategy: Design and implement robust data pipelines and synthetic data generation strategies to train high-performance models.

Qualifications

  • Education: PhD or Master’s degree in Computer Science, Mathematics, Statistics, or a related field with a focus on Machine Learning.
  • Experience: Minimum 5+ years of experience in research roles within top-tier tech companies, research labs, or academic institutions.
  • Technical Stack: Proficiency in Python, C++, and experience with distributed computing systems (e.g., Kubernetes, Apache Spark).
  • Modeling: Deep expertise in Deep Learning, Natural Language Processing (NLP), and Transformer architectures.
  • Research Skills: Proven track record of publishing in peer-reviewed venues and a strong understanding of research methodologies.
  • Problem Solving: Exceptional ability to solve complex, ambiguous problems with innovative algorithmic solutions.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning NLP Transformers LLM GPT CUDA Kubernetes Research PhD Stanford MIT

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