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Senior Generative AI Architect (2026 Vision)

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

Job Description

Join the vanguard of the artificial intelligence revolution. Nexus Horizon Labs is seeking a visionary Senior Generative AI Architect to lead the development of the next generation of multimodal foundation models. As we prepare for the transformative capabilities of 2026, you will be responsible for architecting scalable AI systems that redefine human-machine interaction.

You will work in a high-performance environment focused on cutting-edge research, deploying state-of-the-art Large Language Models (LLMs), and optimizing inference pipelines for real-world applications. If you are passionate about the future of AI and want to build systems that matter, this is your opportunity to shape the future.

Responsibilities

  • Architect and train state-of-the-art foundation models (LLMs, VLMs) tailored for enterprise-scale deployment.
  • Optimize model inference and training pipelines to reduce latency and cost using techniques like quantization and distillation.
  • Design robust evaluation frameworks and benchmarks to measure model performance against 2026 industry standards.
  • Collaborate cross-functionally with product, engineering, and design teams to translate technical breakthroughs into user-centric features.
  • Lead research initiatives into emerging modalities such as audio, video, and spatial computing integration.
  • Ensure ethical AI practices, data privacy, and safety protocols are embedded in the core architecture.

Qualifications

  • Master’s or PhD in Computer Science, Machine Learning, or a related quantitative field.
  • 5+ years of professional experience in deep learning, with at least 2 years focusing on Generative AI or Large Language Models.
  • Expert proficiency in PyTorch, TensorFlow, or JAX.
  • Deep understanding of transformer architectures, attention mechanisms, and fine-tuning strategies (PEFT, LoRA).
  • Proven track record of deploying models to production using cloud infrastructure (AWS, GCP, or Azure).
  • Strong background in MLOps, data pipelines, and model versioning.
  • Excellent communication skills and the ability to mentor junior engineers and researchers.

Required Skills

Generative AI Large Language Models (LLMs) PyTorch TensorFlow MLOps Transformer Architecture Deep Learning Python CUDA Reinforcement Learning from Human Feedback (RLHF) Model Optimization

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