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Senior AI Architect - 2026 Horizon

Synapse Future Tech
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
5 Juli 2026
Deadline
5 Jul 2027

Job Description

Are you ready to architect the intelligence layer of the next decade? Synapse Future Tech is looking for a visionary Senior AI Architect to lead our research into generative models and autonomous agents. As we push the boundaries of what is possible in 2026, you will define the technical roadmap for our proprietary AI ecosystem.

We are not just building software; we are building the future of human-machine interaction. If you are passionate about Large Language Models (LLMs), reinforcement learning, and ethical AI deployment, this is your opportunity to shape the industry standard.

Responsibilities

  • Architect Next-Gen AI Systems: Design and implement scalable, fault-tolerant systems for training and deploying state-of-the-art Large Language Models and multimodal agents.
  • Model Optimization: Lead efforts in model quantization, distillation, and latency optimization to ensure real-time performance in edge environments.
  • R&D Leadership: Conduct cutting-edge research in novel neural architectures, contributing to open-source communities and patentable innovations.
  • Infrastructure Scalability: Build and maintain robust MLOps pipelines using Kubernetes and cloud-native technologies to handle petabyte-scale datasets.
  • AI Ethics & Safety: Implement guardrails and safety protocols to ensure AI outputs align with human values and regulatory standards.
  • Team Mentorship: Guide a team of junior data scientists and engineers, fostering a culture of continuous learning and technical excellence.

Qualifications

  • Education: Master’s or PhD in Computer Science, Machine Learning, or a related quantitative field.
  • Technical Mastery: Deep expertise in Python, PyTorch, TensorFlow, and Hugging Face Transformers.
  • Experience: 5+ years of professional experience in building production-level AI systems, with at least 2 years specifically focused on LLMs or generative AI.
  • Mathematical Proficiency: Strong foundation in linear algebra, calculus, and probability theory.
  • System Design: Proven ability to design distributed systems capable of high concurrency and low latency.
  • Communication: Exceptional ability to translate complex technical concepts into clear strategies for stakeholders.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning LLMs NLP MLOps Kubernetes Cloud Computing System Design

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