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Artificial Intelligence 🏢 Full Time ⭐️ Verified

Senior AI Architect at 2026

2026
San Francisco
Estimated Salary
USD 160.000 – USD 240.000
New
Live Update
1 Juli 2026
Deadline
1 Jul 2027

Job Description

Are you ready to architect the future of intelligence? 2026 is seeking a visionary Senior AI Architect to lead the development of our proprietary next-generation neural networks and autonomous systems.


At 2026, we are building the foundational technologies for the year 2026 and beyond. We are looking for engineers who don't just follow trends but set them. If you have a deep understanding of deep learning, distributed systems, and a passion for solving unsolved problems, this is your stage.


Why join 2026?

  • Work on cutting-edge AI that will define the next decade.
  • Competitive equity package and top-tier compensation.
  • Remote-first culture with flexible hours.
  • Access to state-of-the-art computing infrastructure.

Responsibilities

  • Lead Architecture: Design and implement scalable, high-performance AI infrastructure for the 2026 core platform.
  • Model Development: Spearhead the research and deployment of Large Language Models (LLMs) and reinforcement learning agents.
  • Team Mentorship: Guide junior engineers and researchers, conducting code reviews and architectural discussions to ensure best practices.
  • Performance Optimization: Optimize model inference speeds and reduce latency in real-time applications.
  • Roadmap Planning: Collaborate with product leaders to define the technical roadmap for upcoming 2026 product releases.
  • Collaboration: Work closely with cross-functional teams including data engineers, product managers, and security experts.

Qualifications

  • Education: MS or PhD in Computer Science, Mathematics, or a related field with a focus on AI/ML.
  • Experience: 5+ years of professional experience in machine learning engineering or applied AI research.
  • Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX. Strong experience with distributed computing (Kubernetes, Ray) and cloud platforms (AWS, GCP).
  • Domain Knowledge: Deep understanding of NLP, Computer Vision, or Generative AI architectures.
  • Problem Solving: Proven track record of solving complex, ambiguous engineering problems.
  • Communication: Excellent written and verbal communication skills for technical and non-technical stakeholders.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning NLP Computer Vision Kubernetes AWS GCP Distributed Systems CUDA Reinforcement Learning

Ready to Take This Challenge?

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