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Senior AI Architect: Neural-Synthetic Integration

Omni-Next Dynamics
San Francisco
Estimated Salary
USD 190.000 – USD 260.000
Live Update
17 Mei 2026
Deadline
17 Mei 2027

Job Description

Are you ready to architect the intelligence layer of the 2026 decade? Omni-Next Dynamics is seeking a visionary Senior AI Architect to lead the development of next-generation synthetic intelligence systems. In this pivotal role, you will bridge the gap between advanced neural networks and high-fidelity synthetic data generation, creating robust infrastructure for autonomous decision-making.

We are not just building software; we are defining the paradigm of tomorrow. If you thrive in a high-performance environment and want to push the boundaries of what is possible with Artificial General Intelligence (AGI), we want to hear from you.

Responsibilities

  • Architect Scalable AI Pipelines: Design and implement end-to-end machine learning systems optimized for massive data throughput and low-latency inference.
  • Lead Research Initiatives: Spearhead research into Neural-Synthetic Integration (NSI) technologies to enhance model robustness and reduce hallucination rates.
  • Hybrid System Optimization: Collaborate with quantum computing researchers to hybridize classical AI models with quantum algorithms.
  • Infrastructure Scaling: Oversee the deployment of models on distributed cloud environments, ensuring 99.99% uptime and seamless scalability.
  • Tech Strategy: Define the technical roadmap for our AI infrastructure, evaluating new frameworks and hardware accelerators.

Qualifications

  • Education: Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
  • Experience: 7+ years of experience in machine learning engineering, system architecture, and software development.
  • Technical Expertise: Deep proficiency in Python, C++, and frameworks such as TensorFlow, PyTorch, or JAX.
  • Cloud Mastery: Extensive experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
  • Quantum Awareness: Familiarity with quantum computing concepts and libraries (Qiskit, Cirq) is a strong plus.

Required Skills

Python TensorFlow PyTorch Cloud Computing Distributed Systems System Architecture Machine Learning AI Engineering Kubernetes Docker AWS GCP

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