Job Description
We are seeking a visionary Senior AI Architect to spearhead the development of next-generation artificial intelligence systems. In this pivotal role, you will define the technical roadmap for 2026 and beyond, building the infrastructure that powers the future of generative AI and autonomous systems. If you are passionate about pushing the boundaries of what is possible with Large Language Models (LLMs) and Neural Networks, we want to hear from you.
Why Join Nexus Horizon?
- Work on cutting-edge research that will define the industry standard for the next decade.
- Competitive compensation package and equity opportunities.
- Flexible remote-first policy with a hub in San Francisco.
Our mission is to bridge the gap between theoretical AI and practical, scalable real-world applications.
Responsibilities
- Pioneer R&D: Lead the architecture and implementation of proprietary multimodal AI models, focusing on scalability and ethical AI principles.
- System Optimization: Design and deploy high-performance inference pipelines capable of handling billions of requests with low latency.
- Strategic Planning: Collaborate with the CTO to define the 2026 technology roadmap, identifying emerging trends in Generative AI and Quantum Computing integration.
- Team Leadership: Mentor a team of brilliant data scientists and ML engineers, fostering a culture of innovation and continuous learning.
- Model Evaluation: Establish rigorous benchmarks for model accuracy, robustness, and safety to ensure production-grade reliability.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- Experience: 5+ years of professional experience in AI/ML architecture, with at least 2 years leading technical teams.
- Technical Skills: Deep expertise in Python, PyTorch, TensorFlow, and C++. Proven experience with distributed systems and cloud platforms (AWS/GCP/Azure).
- Domain Knowledge: Strong background in Natural Language Processing (NLP), Transformer architectures, or Reinforcement Learning.
- Problem Solving: Ability to translate complex business problems into elegant technical solutions.