Job Description
Are you ready to define the technological landscape of 2026? Nexus Horizons is seeking a visionary Senior AI Architect to lead our cutting-edge research division. We are building the next generation of autonomous systems and predictive intelligence, and we need a leader who can bridge the gap between theoretical breakthroughs and scalable production code.
In this role, you will not just maintain existing systems; you will architect the future. You will collaborate with world-class engineers and data scientists to deploy models that redefine industry standards. If you are passionate about the trajectory of AI and want to leave a lasting legacy in the tech world, this is your opportunity.
Why Join Us?
- Work on high-impact projects that shape the future.
- Competitive compensation package with equity options.
- Access to state-of-the-art hardware and computing clusters.
- Flexible remote and hybrid work options in the heart of San Francisco.
Responsibilities
- Architect Scalable ML Systems: Design and implement robust, fault-tolerant machine learning infrastructure capable of handling petabyte-scale data streams.
- Strategic Roadmapping: Define the technical roadmap for AI capabilities, anticipating trends in Generative AI and Autonomous Agents for the 2026 era.
- Model Optimization: Lead initiatives to optimize model latency, accuracy, and energy efficiency across distributed cloud environments.
- Cross-Functional Leadership: Partner with product managers and software engineers to translate complex research into actionable product features.
- R&D Mentorship: Mentor junior architects and data scientists, fostering a culture of continuous learning and technical excellence.
- Compliance & Ethics: Ensure all AI deployments adhere to the highest standards of ethical AI, data privacy, and regulatory compliance.
Qualifications
- Education: Master’s or PhD in Computer Science, Machine Learning, or a related technical field.
- Experience: Minimum of 7+ years of experience in software engineering and machine learning architecture.
- Technical Stack: Proficiency in Python, C++, and experience with deep learning frameworks (TensorFlow, PyTorch, JAX).
- Cloud Expertise: Deep understanding of cloud architecture (AWS, GCP, or Azure) and containerization technologies (Kubernetes, Docker).
- Domain Knowledge: Strong background in Natural Language Processing (NLP) or Computer Vision is highly preferred.
- Problem Solving: Demonstrated ability to tackle ambiguous problems and deliver innovative solutions under tight deadlines.