Job Description
Nexus Horizon is pioneering the technologies that will define the year 2026. We are seeking a visionary Senior AI Architect to lead our next-generation neural infrastructure. If you are passionate about building the cognitive engines of the future and shaping the trajectory of artificial general intelligence, we want to meet you.
In this role, you will design and implement scalable machine learning systems that power our core products. You will work at the intersection of theoretical research and practical engineering, ensuring our models are not only powerful but also efficient and safe.
Why Join Nexus Horizon?
- Work on cutting-edge technology that will define the 2026 landscape.
- Competitive equity package and performance bonuses.
- Flexible remote-first policy with a hub in the heart of SF.
- Access to state-of-the-art compute infrastructure.
Are you ready to architect the future? Apply today.
Responsibilities
- Architect Design: Design and oversee the implementation of complex AI and machine learning architectures, including large language models (LLMs) and generative adversarial networks.
- System Optimization: Drive the optimization of model inference and training pipelines to reduce latency and improve cost-efficiency on massive scales.
- Technical Leadership: Mentor a team of junior engineers and data scientists, fostering a culture of innovation and rigorous engineering standards.
- R&D Collaboration: Partner with our research division to translate theoretical breakthroughs into production-ready software solutions.
- Model Governance: Establish best practices for model monitoring, bias detection, and ethical AI deployment.
Qualifications
- Experience: 5+ years of experience in software engineering, with at least 3 years specializing in AI/ML architecture.
- Technical Skills: Proficiency in Python, PyTorch, or TensorFlow; experience with distributed computing frameworks (Kubernetes, Ray, or Spark).
- Deep Learning: Strong understanding of deep learning principles, neural network architectures, and optimization techniques.
- Education: MS or PhD in Computer Science, Mathematics, or a related field is strongly preferred.
- Problem Solving: Exceptional ability to solve complex, ambiguous problems and make data-driven architectural decisions.