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Future Tech Architect (AI/ML) - Shaping 2026

Nexus Future Systems
San Francisco
Estimated Salary
USD 200.000 – USD 300.000
New
Live Update
30 Juni 2026
Deadline
30 Jun 2027

Job Description

The Future is Here. Nexus Future Systems is seeking a visionary Future Tech Architect to lead the development of next-generation Artificial Intelligence and Machine Learning infrastructure. As we look ahead to the technological landscape of 2026, we need a pioneer who can bridge the gap between theoretical research and scalable engineering.

In this role, you will define the architectural standards for our AI-driven products, ensuring they are robust, scalable, and ethically sound. You will work at the forefront of Generative AI, Natural Language Processing, and autonomous systems.

Why Join Us?

  • Work on cutting-edge technology that defines the future.
  • Competitive compensation package and equity options.
  • Flexible remote-first policy with a San Francisco hub.

Responsibilities

  • Design and implement scalable AI/ML architectures capable of handling petabyte-scale data.
  • Lead the research and integration of emerging AI models (e.g., GPT-5, Autonomous Agents) for production deployment.
  • Collaborate with cross-functional teams to translate complex data science concepts into user-friendly applications.
  • Establish best practices for data governance, model explainability, and ethical AI usage.
  • Optimize existing algorithms to reduce latency and increase throughput for real-time applications.
  • Conduct technical due diligence on emerging technologies to guide our strategic roadmap.

Qualifications

  • Master’s or PhD in Computer Science, Mathematics, or a related technical field (PhD preferred).
  • Minimum of 5 years of experience in software engineering, data science, or AI research.
  • Deep proficiency in Python, PyTorch, TensorFlow, and distributed computing frameworks (Spark, Ray).
  • Proven experience designing and deploying Large Language Models (LLMs) and Generative AI applications.
  • Strong understanding of MLOps, cloud infrastructure (AWS, GCP, or Azure), and containerization (Docker, Kubernetes).
  • Exceptional problem-solving skills and the ability to thrive in a fast-paced, high-stakes environment.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning NLP MLOps AWS Kubernetes Docker Generative AI Data Science System Architecture

Ready to Take This Challenge?

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