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Information Technology 🏒 Full Time ⭐️ Verified

Senior AI Architect (2026 Vision)

Nexus Future Labs
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
New
Live Update
13 Juli 2026
Deadline
13 Jul 2027

Job Description

We are Nexus Future Labs, a pioneer in next-generation intelligence systems. As we accelerate towards our 2026 roadmap, we are seeking a visionary Senior AI Architect to lead the development of our proprietary Large Language Model (LLM) infrastructure and generative AI frameworks.

In this role, you will not just build models; you will architect the cognitive core of our enterprise solutions. You will bridge the gap between theoretical AI research and scalable production deployment, ensuring our systems are robust, ethical, and future-proof.

If you are passionate about pushing the boundaries of what is possible in 2026 and beyond, we want to hear from you.

Responsibilities

  • Design and implement scalable Generative AI pipelines and LLM architectures tailored for enterprise use cases.
  • Optimize model inference latency and cost-efficiency using techniques such as quantization, pruning, and distillation.
  • Lead the MLOps strategy, integrating CI/CD for machine learning models and managing model lifecycle from training to deployment.
  • Collaborate with data scientists and engineers to fine-tune foundation models on proprietary datasets.
  • Ensure AI systems adhere to strict ethical guidelines and safety protocols regarding bias and transparency.
  • Stay ahead of emerging AI trends (e.g., Multimodal AI, Autonomous Agents) and evaluate their applicability to Nexus products.

Qualifications

  • Master’s or PhD in Computer Science, Machine Learning, or a related quantitative field (PhD preferred).
  • Minimum of 5 years of experience in AI/ML engineering, with at least 2 years focused on LLMs or Generative AI.
  • Expert proficiency in Python, PyTorch, and TensorFlow.
  • Strong understanding of NLP concepts, including Transformer architectures, RAG (Retrieval-Augmented Generation), and fine-tuning strategies.
  • Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
  • Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.

Required Skills

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

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