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Information Technology 🏢 Full Time ⭐️ Verified

Senior AI Architect

Nebula Dynamics
San Francisco
Estimated Salary
USD 160.000 – USD 240.000
New
Live Update
28 Juni 2026
Deadline
28 Jun 2027

Job Description

Are you ready to shape the future of artificial intelligence? Nebula Dynamics is seeking a visionary Senior AI Architect to lead our next-generation machine learning initiatives. As we prepare to redefine the landscape of tech in the coming years, you will be at the helm of designing scalable, robust AI systems that power our enterprise solutions.

We are looking for a thought leader who not only possesses deep technical expertise but also has the strategic mindset to mentor a high-performing engineering team. If you are passionate about pushing the boundaries of what's possible with Large Language Models (LLMs) and Neural Networks, we want to hear from you.

Responsibilities

  • Design and architect scalable machine learning pipelines and infrastructure to support production-grade AI applications.
  • Lead the research and implementation of cutting-edge algorithms in Natural Language Processing (NLP) and Computer Vision.
  • Mentor and guide junior engineers and data scientists, fostering a culture of innovation and continuous learning.
  • Collaborate with cross-functional teams—including product managers, data engineers, and designers—to define technical requirements and roadmap features.
  • Optimize existing models for speed, accuracy, and resource efficiency, ensuring high availability and low latency.
  • Stay abreast of the latest advancements in AI research and evaluate their applicability to Nebula Dynamics' products.

Qualifications

  • Ph.D. or Master’s degree in Computer Science, Mathematics, or a related quantitative field.
  • 7+ years of professional experience in software engineering and machine learning, with at least 3 years in a senior architecture role.
  • Deep proficiency in Python, C++, and modern deep learning frameworks such as PyTorch or TensorFlow.
  • Extensive experience with distributed systems, cloud platforms (AWS/GCP), and containerization technologies (Docker/Kubernetes).
  • Strong understanding of MLOps practices, including model versioning, CI/CD, and monitoring.
  • Excellent problem-solving skills and the ability to translate complex business requirements into technical specifications.

Required Skills

Python PyTorch TensorFlow Machine Learning NLP Cloud Computing AWS Docker Kubernetes MLOps

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