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Information Technology 🏒 Full Time ⭐️ Verified

Senior AI Architect: 2026 Vision

Nexus Future Labs
San Francisco
Estimated Salary
USD 160.000 – USD 230.000
Live Update
30 Juni 2026
Deadline
30 Jun 2027

Job Description

We are pioneering the technological frontier of the future. As we look toward the horizon of 2026, we are seeking a visionary Senior AI Architect to lead our advanced machine learning initiatives. This is not just a job; it is a mission to engineer the intelligent systems that will define the next era of human-computer interaction.

At Nexus Future Labs, we believe in pushing boundaries. You will work with state-of-the-art generative models, predictive analytics, and next-gen neural architectures to solve complex, global problems. If you are ready to build the tools of tomorrow, today, we want to hear from you.

Responsibilities

  • Architect Scalable Solutions: Design and deploy robust, high-performance AI architectures capable of handling enterprise-scale data streams.
  • Lead R&D Initiatives: Spearhead research into Large Language Models (LLMs), Computer Vision, and autonomous agents to stay ahead of industry trends.
  • System Optimization: Continuously refine and optimize models for reduced latency, improved throughput, and maximum cost-efficiency.
  • Product Integration: Collaborate with product and engineering teams to seamlessly integrate AI capabilities into our core software platforms.
  • Talent Development: Mentor junior engineers and data scientists, fostering a culture of technical excellence and innovation.

Qualifications

  • Education: Master’s or Ph.D. in Computer Science, Artificial Intelligence, Mathematics, or a related technical field.
  • Experience: 5+ years of professional experience in AI/ML engineering, with at least 2 years in a senior or lead technical role.
  • Technical Skills: Deep proficiency in Python, PyTorch, TensorFlow, and modern MLOps tools (Kubeflow, MLflow).
  • Model Expertise: Extensive experience training, fine-tuning, and deploying large-scale neural networks.
  • Cloud Mastery: Strong experience with cloud infrastructure (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).

Required Skills

Python TensorFlow PyTorch AWS GCP Machine Learning Deep Learning NLP MLOps AI Architecture

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