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Artificial Intelligence 🏢 Full Time ⭐️ Verified

Senior AI Research Engineer - Generative Models | San Francisco, CA

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

Job Description

Are you ready to define the future of Artificial Intelligence? Neural Nexus Labs is seeking a visionary Senior AI Research Engineer to lead our next-generation generative model initiatives. We are building the infrastructure that powers tomorrow's intelligent applications, and we need a technical expert to push the boundaries of Large Language Models (LLMs) and multimodal AI.

In this role, you will collaborate with world-class researchers and engineers to design, train, and deploy state-of-the-art models. If you are passionate about deep learning, possess a strong mathematical background, and want to solve complex problems at scale, we want to meet you.

Why Join Us?

  • Work with cutting-edge technology in a high-growth environment.
  • Competitive compensation and equity package.
  • Flexible remote-first culture with a central hub in San Francisco.
  • Opportunity to publish in top-tier conferences (NeurIPS, ICML, ICLR).

Responsibilities

  • Design and implement novel deep learning architectures for natural language processing and computer vision tasks.
  • Optimize existing models for inference speed and memory efficiency on cloud-scale hardware.
  • Conduct rigorous experimentation and hyperparameter tuning to improve model accuracy and robustness.
  • Collaborate with product teams to translate research findings into production-ready features.
  • Stay abreast of the latest academic literature and industry trends to integrate best practices into our pipeline.
  • Mentor junior researchers and engineers, fostering a culture of continuous learning and innovation.

Qualifications

  • Ph.D. or Master's degree in Computer Science, Mathematics, or a related field with a focus on AI/ML.
  • Proven experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX.
  • Strong proficiency in Python and C++ for high-performance computing.
  • Deep understanding of transformer architectures, attention mechanisms, and optimization techniques.
  • Experience with distributed training and model serving platforms (e.g., Kubernetes, Ray, SageMaker).
  • Track record of publishing research in reputable conferences or patents in AI/ML.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning NLP LLMs CUDA Kubernetes Cloud Computing

Ready to Take This Challenge?

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