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Senior AI Architect - Shaping the Future (2026)

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

Job Description

Are you ready to architect the technological landscape of 2026? Apex 2026 is seeking a visionary Senior AI Architect to join our elite team in San Francisco. We are building the foundational AI systems that will define the next decade. If you thrive on complexity and want to leave a lasting impact on the future of technology, this is your opportunity.

As a key member of our R&D division, you will bridge the gap between theoretical AI research and scalable production systems. We are looking for a problem solver who isn't afraid to push boundaries and redefine what's possible in Artificial Intelligence.

Responsibilities

  • Architect Scalable ML Systems: Design and implement robust, production-grade machine learning pipelines and infrastructure capable of handling petabyte-scale data.
  • Pioneering Research: Lead cutting-edge research in Natural Language Processing (NLP) and Generative AI to solve complex, real-world problems.
  • Model Optimization: Optimize deep learning models for speed, accuracy, and resource efficiency, reducing latency in real-time applications.
  • Collaborative Innovation: Work closely with cross-functional teams of data scientists, engineers, and product managers to translate business needs into technical solutions.
  • Mentorship: Guide junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
  • Deployment & MLOps: Manage the end-to-life cycle of ML models, from experimental training to deployment and monitoring in cloud environments.

Qualifications

  • Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, or a related field.
  • Experience: 5+ years of professional experience in Machine Learning or Artificial Intelligence.
  • Technical Stack: Strong proficiency in Python, PyTorch, TensorFlow, and SQL.
  • Specialization: Deep experience with LLMs, Transformers, or Generative AI models.
  • Cloud Expertise: Hands-on experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
  • Problem Solving: Demonstrated ability to troubleshoot complex algorithms and optimize system performance under pressure.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning NLP SQL AWS Docker Kubernetes MLOps LLMs Generative AI

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