Job Description
We are on a mission to architect the intelligent systems of 2026. Nexus Horizon Systems is seeking a visionary Senior AI Architect to lead our next-generation generative AI initiatives. You will be at the forefront of the AI revolution, designing scalable architectures that power the future of enterprise automation and human-computer interaction. If you are passionate about pushing the boundaries of Large Language Models (LLMs), AI Agents, and multimodal systems, we want to hear from you.
Why Join Us?
- Work with state-of-the-art technology in a cutting-edge environment.
- Competitive compensation package and equity options.
- Flexible remote-first policy with a hub in the heart of San Francisco.
- Opportunity to define the technical roadmap for the AI landscape of 2026.
Responsibilities
- Architectural Leadership: Design and implement robust, scalable, and secure AI infrastructure capable of handling enterprise-grade workloads.
- Generative AI Development: Spearhead the development and fine-tuning of proprietary Large Language Models (LLMs) and generative models using PyTorch and TensorFlow.
- AI Agent Integration: Build autonomous AI agents that can perform complex tasks, leveraging tools like LangChain and AutoGPT frameworks.
- Optimization & Efficiency: Oversee model optimization strategies, including quantization, pruning, and inference acceleration to reduce latency and costs.
- R&D Strategy: Stay ahead of emerging trends in AI for 2026, evaluating new research papers and technologies to integrate them into our product ecosystem.
- Collaboration: Partner with cross-functional teams (Product, Engineering, Data Science) to translate business requirements into technical AI solutions.
Qualifications
- Education: Master’s or PhD in Computer Science, Machine Learning, or a related technical field (or equivalent professional experience).
- Core Expertise: Deep understanding of Deep Learning, Natural Language Processing (NLP), and Generative Adversarial Networks (GANs).
- Programming: Proficiency in Python, with strong experience in C++ or Rust for high-performance computing tasks.
- Frameworks: Extensive experience with PyTorch, TensorFlow, Hugging Face Transformers, and distributed training frameworks (Ray, Dask).
- Cloud & MLOps: Proven track record deploying models on cloud platforms (AWS, GCP, or Azure) using MLOps tools like MLflow, Kubeflow, or Sagemaker.
- Problem Solving: Exceptional analytical skills with a demonstrated ability to solve complex, unstructured problems in novel ways.