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Information Technology 🏢 Full Time ⭐️ Verified

Senior AI Infrastructure Engineer | 2026 Vision

Apex Horizon Solutions
San Francisco
Estimated Salary
USD 180.000 – USD 240.000
New
Live Update
22 Mei 2026
Deadline
22 Mei 2027

Job Description

We are seeking a visionary Senior AI Infrastructure Engineer to lead the architectural design of our next-generation systems. As we prepare for the 2026 roadmap, we are looking for a technical leader who can bridge the gap between cutting-edge machine learning research and scalable, production-grade infrastructure. You will be instrumental in building the digital backbone that will support our enterprise clients for years to come.


Why Join Us?

  • Work on the forefront of the AI revolution.
  • Competitive compensation and equity package.
  • Flexible remote-first culture with a hub in San Francisco.
  • Access to state-of-the-art computing resources.

If you are passionate about building resilient systems and defining the future of tech, we want to hear from you.

Responsibilities

  • Architecture Design: Design and implement scalable, high-performance AI infrastructure pipelines capable of handling petabyte-scale data.
  • Model Deployment: Oversee the deployment and orchestration of ML models using Kubernetes and serverless architectures.
  • Performance Optimization: Continuously monitor, optimize, and troubleshoot system latency and resource utilization.
  • Collaboration: Partner with data scientists and ML engineers to translate research into production-ready code.
  • Security & Compliance: Implement rigorous security protocols and ensure compliance with industry standards.

Qualifications

  • Education: Bachelor’s degree in Computer Science, Engineering, or a related field (Master’s preferred).
  • Experience: 5+ years of experience in software engineering, with at least 3 years focused on machine learning infrastructure.
  • Programming: Expert proficiency in Python, with deep knowledge of PyTorch or TensorFlow.
  • DevOps: Strong experience with Docker, Kubernetes, and cloud platforms (AWS, GCP, or Azure).
  • Tools: Familiarity with CI/CD pipelines, Terraform, and monitoring tools (Prometheus, Grafana).

Required Skills

Python PyTorch TensorFlow Kubernetes Docker AWS GCP MLOps CI/CD Machine Learning System Architecture

Ready to Take This Challenge?

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