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Information Technology 🏒 Full Time ⭐️ Verified

Senior AI Infrastructure Architect

Nexus Horizon
San Francisco
Estimated Salary
USD 185.000 – USD 260.000
New
Live Update
12 Mei 2026
Deadline
12 Mei 2027

Job Description

The Future is Here. Nexus Horizon is pioneering the next generation of intelligent systems for the year 2026 and beyond. We are seeking a visionary Senior AI Infrastructure Architect to design the backbone of our neural networks and scalable machine learning platforms. If you are passionate about pushing the boundaries of what is possible in AI and want to shape the infrastructure of tomorrow, we want to meet you.

Join a diverse team of engineers, researchers, and strategists working on high-impact projects that redefine human-machine interaction.

Responsibilities

  • Design Scalable Architectures: Architect robust, scalable, and fault-tolerant AI infrastructure capable of handling petabyte-scale data processing.
  • Lead R&D Initiatives: Spearhead research into next-generation machine learning models, including generative AI and quantum-ready algorithms.
  • Optimize Performance: Continuously monitor and optimize inference latency, model accuracy, and resource utilization across distributed systems.
  • Collaborate with Cross-Functional Teams: Work closely with data scientists, product managers, and security experts to integrate AI solutions seamlessly into our products.
  • Ethical AI Governance: Establish and enforce guidelines to ensure AI systems are fair, transparent, and unbiased.
  • Mentorship: Guide junior engineers and architects in best practices for cloud-native AI development.

Qualifications

  • Education: Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related technical field (or equivalent practical experience).
  • Experience: 7+ years of experience in software engineering, with at least 3 years in AI/ML infrastructure or MLOps.
  • Technical Skills: Proficiency in Python, TensorFlow, PyTorch, and distributed computing frameworks (e.g., Apache Spark, Kubernetes).
  • Cloud Mastery: Deep expertise in AWS, Google Cloud Platform (GCP), or Azure, including serverless and containerization technologies.
  • Problem Solving: Proven track record of solving complex technical challenges and optimizing system performance under high load.
  • Communication: Excellent verbal and written communication skills with the ability to translate technical concepts for non-technical stakeholders.

Required Skills

Python TensorFlow PyTorch AWS GCP Kubernetes Docker MLOps Machine Learning Distributed Systems

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