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Senior Generative AI Architect

Nexus Horizon
San Francisco
Estimated Salary
USD 185.000 – USD 260.000
New
Live Update
30 Juni 2026
Deadline
30 Jun 2027

Job Description

Shape the Technological Landscape of 2026 and Beyond.

Nexus Horizon is at the forefront of the generative revolution, pioneering the next generation of intelligent systems. We are seeking a visionary Senior Generative AI Architect to lead the development of scalable, high-performance AI models that will define the future of our industry.

In this pivotal role, you will bridge the gap between cutting-edge research and production-grade engineering. You will architect systems capable of processing billions of parameters in real-time, ensuring our solutions are not only powerful but also responsible and efficient.

Why Join Nexus Horizon?

  • Impact: Work on projects that will be integral to the infrastructure of 2026.
  • Autonomy: Lead architectural decisions in a culture that rewards innovation over bureaucracy.
  • Growth: Access to the latest hardware, research libraries, and top-tier talent in the Bay Area.

If you are ready to push the boundaries of what is possible in AI, we want to hear from you.

Responsibilities

  • Design and implement scalable generative models (LLMs, diffusion models) using Python and modern frameworks.
  • Optimize model inference speed and reduce latency for real-time applications.
  • Collaborate with research teams to translate theoretical models into production-ready software.
  • Build and maintain robust data pipelines for training and fine-tuning large datasets.
  • Ensure system reliability, security, and compliance with AI ethical guidelines.
  • Guide junior engineers and architects in best practices for machine learning engineering.

Qualifications

  • Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related technical field.
  • Minimum of 5+ years of professional experience in AI/ML engineering, with a focus on Generative AI.
  • Strong proficiency in Python, PyTorch, TensorFlow, or JAX.
  • Deep understanding of distributed systems, cloud architecture (AWS/GCP), and containerization (Docker/Kubernetes).
  • Experience with MLOps tools (MLflow, Kubeflow, Airflow) and model serving platforms.
  • Excellent problem-solving skills and the ability to communicate complex technical concepts to diverse stakeholders.

Required Skills

Python PyTorch TensorFlow AWS Docker Kubernetes MLOps LLMs Generative AI Machine Learning NLP

Ready to Take This Challenge?

Make sure your resume is ready. Submit your application now before the deadline.

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