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Senior AI Architect (2026 Initiative)

Apex Neural Systems
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
New
Live Update
30 Juni 2026
Deadline
30 Jun 2027

Job Description

Join the 2026 Initiative: Architecting the Future of Intelligence.

Apex Neural Systems is pioneering the next generation of Artificial General Intelligence (AGI) and autonomous decision-making systems. We are looking for a visionary Senior AI Architect to lead our core infrastructure, ensuring our models are scalable, secure, and ready for the demands of the year 2026 and beyond.

If you thrive in high-stakes environments, love solving complex system design problems, and want to define the roadmap for the future of AI, we want to meet you.

Why Join Us?

  • Work on groundbreaking models that will define the industry standard.
  • Competitive equity package with performance bonuses.
  • Flexible remote-first culture with hubs in SF and NYC.
  • Access to cutting-edge hardware and research facilities.

Responsibilities

  • Design and implement scalable distributed machine learning pipelines capable of handling petabyte-scale data.
  • Lead the architectural strategy for our proprietary Neural Processing Units (NPUs) integration.
  • Oversee the deployment of Large Language Models (LLMs) into production environments, ensuring high availability and low latency.
  • Collaborate with cross-functional teams of researchers, engineers, and product managers to translate research into production-ready applications.
  • Mentor junior architects and engineers, fostering a culture of innovation and technical excellence.
  • Identify and mitigate potential security risks and biases in AI models.

Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field (PhD preferred).
  • 10+ years of experience in software engineering and machine learning architecture.
  • Deep expertise in Python, TensorFlow, PyTorch, and distributed systems (Kubernetes, Docker).
  • Proven track record of deploying production-grade AI systems at scale.
  • Strong understanding of MLOps, data engineering, and cloud infrastructure (AWS, GCP, or Azure).
  • Experience with edge computing and hardware acceleration (FPGA/ASIC) is a plus.
  • Excellent communication skills with the ability to articulate complex technical concepts to non-technical stakeholders.

Required Skills

Artificial Intelligence Machine Learning Python TensorFlow PyTorch Distributed Systems MLOps Kubernetes Cloud Architecture System Design

Ready to Take This Challenge?

Make sure your resume is ready. Submit your application now before the deadline.

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