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Information Technology 🏢 Full Time ⭐️ Verified

Lead AI Infrastructure Engineer (2026 Vision)

Nexus Horizon Labs
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
New
Live Update
22 Mei 2026
Deadline
22 Mei 2027

Job Description

Nexus Horizon Labs is redefining the boundaries of artificial intelligence. We are currently seeking a visionary Lead AI Infrastructure Engineer to architect the backbone of our 2026 roadmap. In this pivotal role, you will bridge the gap between cutting-edge machine learning research and scalable, production-grade systems. If you are passionate about building the infrastructure that powers the next generation of intelligent applications, we want to hear from you.

Why Join Us?

  • Work on high-impact projects that shape the future of tech.
  • Competitive compensation and equity package.
  • Flexible remote-first culture with a collaborative hub in San Francisco.

Responsibilities

  • Architect Scalable Systems: Design and implement high-throughput, low-latency inference pipelines for Large Language Models (LLMs) and generative AI agents.
  • Optimize Compute Resources: Spearhead the optimization of GPU clusters and distributed training environments to reduce costs and improve performance.
  • Cloud-Native Development: Build and maintain robust cloud infrastructure using AWS or Google Cloud Platform, ensuring high availability and security.
  • Future-Proofing: Research and integrate emerging technologies such as quantum-ready algorithms and decentralized compute networks.
  • Team Leadership: Mentor a team of backend engineers and data scientists, fostering a culture of innovation and technical excellence.
  • Collaboration: Partner with product and research teams to translate complex AI capabilities into user-friendly applications.

Qualifications

  • Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
  • Experience: 5+ years of experience in software engineering, with a strong focus on backend systems and distributed computing.
  • Programming: Proficiency in Python, Rust, or Go, with deep experience in C++ for high-performance computing.
  • AI/ML Knowledge: Strong understanding of machine learning frameworks (TensorFlow, PyTorch) and model serving architectures.
  • Problem Solving: Proven track record of optimizing system performance and scaling applications to handle millions of requests.
  • Communication: Excellent verbal and written communication skills, capable of explaining complex technical concepts to diverse stakeholders.

Required Skills

Python Rust Go AWS Google Cloud Docker Kubernetes Machine Learning Distributed Systems AI Infrastructure San Francisco

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