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Information Technology 🏢 Full Time ⭐️ Verified

Senior AI Infrastructure Engineer (2026 Horizon)

Nexus Core Technologies
San Francisco
Estimated Salary
USD 165.000 – USD 230.000
Live Update
13 Mei 2026
Deadline
13 Mei 2027

Job Description

Are you ready to architect the digital foundation for the next decade? Nexus Core Technologies is seeking a visionary Senior AI Infrastructure Engineer to join our 2026 Horizon Initiative. As we push the boundaries of generative AI and autonomous systems, you will be responsible for designing resilient, scalable infrastructure that powers our next-generation models.

In this high-impact role, you will bridge the gap between cutting-edge machine learning research and robust production engineering. You will optimize compute clusters, implement edge computing solutions, and ensure our AI models run with millisecond latency at global scale.

Why join us?

  • Work on the forefront of AI development for the 2026 era.
  • Competitive compensation and equity packages.
  • Top-tier benefits and flexible remote-first culture.

Responsibilities

  • Design and implement high-availability cloud infrastructure for large-scale AI workloads.
  • Optimize neural network training pipelines to reduce latency and improve throughput.
  • Collaborate with data scientists to deploy and manage MLOps pipelines using Kubernetes and Docker.
  • Architect scalable storage solutions for unstructured data and vector databases.
  • Ensure system security and compliance with industry standards (SOC2, GDPR).
  • Conduct code reviews and mentor junior engineers on best practices in distributed systems.

Qualifications

  • 5+ years of experience in software engineering or systems architecture, with a focus on AI/ML infrastructure.
  • Strong proficiency in Python, C++, and at least one deep learning framework (PyTorch or TensorFlow).
  • Deep understanding of cloud platforms (AWS, GCP, or Azure).
  • Experience with containerization technologies (Docker, Kubernetes) and CI/CD pipelines.
  • Experience with high-performance computing (HPC) and GPU cluster management.
  • Bachelor’s degree in Computer Science, Engineering, or related field (Master’s preferred).

Required Skills

Python PyTorch TensorFlow Kubernetes Docker AWS GCP Machine Learning MLOps System Design

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