Job Description
Are you ready to architect the intelligence of tomorrow? Nexus Horizon Technologies is seeking a visionary Senior AI Architect to lead our R&D division focused on the 2026 roadmap. We are building the next generation of autonomous systems and are looking for a technical leader who thrives on complexity and innovation.
As a pivotal member of our elite engineering team, you will define the technical strategy for our flagship AI products. This is not just a development role; it is a strategic position where your code will shape the future of enterprise intelligence. We offer a competitive compensation package, equity opportunities, and the chance to work with industry pioneers in the heart of San Francisco.
Why Join Us?
- Work on cutting-edge Large Language Models (LLMs) and generative AI.
- Competitive salary and equity package ($180k - $250k).
- Flexible remote and hybrid work culture.
Responsibilities
- Architect and deploy scalable machine learning pipelines for real-time decision-making and predictive analytics.
- Lead the research and implementation of next-generation neural network architectures tailored for edge computing environments.
- Collaborate with cross-functional product teams to translate business requirements into robust technical solutions.
- Establish best practices for AI governance, model interpretability, and data privacy compliance.
- Mentor junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
- Optimize model inference latency to ensure seamless user experiences in high-traffic applications.
- Stay ahead of industry trends to integrate emerging technologies into our 2026 product roadmap.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Mathematics, or a related technical field.
- 7+ years of professional experience in software engineering with a focus on Artificial Intelligence and Machine Learning.
- Deep proficiency in Python, PyTorch, and TensorFlow.
- Strong experience designing distributed systems capable of handling petabyte-scale data.
- Proven track record of deploying production-grade AI models at scale.
- Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).