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Senior AI/ML Architect (2026 Vision)

Nexus Future Technologies
San Francisco
Estimated Salary
USD 185.000 – USD 260.000
New
Live Update
11 Juli 2026
Deadline
11 Jul 2027

Job Description

We are building the operating system for the next decade. Nexus Future Technologies is seeking a visionary Senior AI/ML Architect to lead our initiative in designing scalable, generative AI infrastructures for the year 2026 and beyond.


As a pivotal member of our R&D division, you will bridge the gap between theoretical breakthroughs and production-grade systems. You will define the architecture for next-gen Large Language Models (LLMs) and ensure our systems are resilient, ethical, and scalable to global demands.


If you are passionate about the future of artificial intelligence and want to shape the technology stack that will define the coming era, we want to hear from you.

Responsibilities

  • Design and implement cutting-edge deep learning architectures for large-scale language models and generative AI systems.
  • Lead the migration of legacy systems to next-generation, high-performance computing clusters.
  • Optimize model inference latency and reduce computational costs by 40% through advanced quantization techniques.
  • Collaborate with cross-functional teams including Product, Security, and Data Engineering to integrate AI into core products.
  • Mentor junior engineers and data scientists, fostering a culture of innovation and technical excellence.
  • Research and prototype novel algorithms to stay ahead of industry trends and regulatory requirements.

Qualifications

  • Master’s or Ph.D. in Computer Science, Mathematics, or a related field with a focus on AI/ML.
  • Minimum of 5-7 years of professional experience in machine learning engineering, preferably at high-scale tech companies.
  • Extensive experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX.
  • Strong proficiency in Python and C++ for high-performance implementation.
  • Proven track record of deploying production-ready AI models with high accuracy and low latency.
  • Experience with MLOps pipelines (e.g., MLflow, Kubeflow) and cloud platforms (AWS/GCP/Azure).

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning NLP MLOps AWS GCP C++ System Design

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