Job Description
Are you ready to architect the intelligence of tomorrow?
Nexus Horizon Solutions is pioneering the next frontier of technology, and we are looking for a visionary Senior AI & Future Systems Architect to join our elite team in San Francisco. In this role, you won't just build models; you will design the cognitive frameworks that will define the technological landscape of 2026 and beyond.
As we prepare for the rapid evolution of generative AI and autonomous systems, we need a leader who can bridge the gap between theoretical innovation and scalable, robust engineering. You will be responsible for spearheading the development of our proprietary AI infrastructure, ensuring our solutions are not only cutting-edge but also ethically grounded and future-proof.
Why Join Nexus Horizon?
- Work on projects that shape the future of enterprise automation.
- Competitive compensation package including equity options.
- State-of-the-art office in the heart of San Francisco.
- Flexible remote-first culture with hybrid work options.
If you are passionate about pushing the boundaries of what is possible in machine learning and systems architecture, we want to hear from you.
Responsibilities
- Architect Future-Proof AI Solutions: Design and deploy scalable machine learning models and neural networks that align with our long-term 2026 strategic roadmap.
- Pipeline Optimization: Build high-throughput data pipelines capable of ingesting and processing massive datasets in real-time to train next-gen algorithms.
- Model Fine-Tuning: Lead the fine-tuning of Large Language Models (LLMs) and multimodal systems to enhance domain-specific accuracy and reduce hallucinations.
- Research & Innovation: Stay at the forefront of AI research, experimenting with emerging technologies such as quantum computing interfaces or neuromorphic engineering.
- Collaboration: Partner with product managers, data scientists, and security experts to integrate AI solutions seamlessly into existing software ecosystems.
- Ethical AI Compliance: Implement rigorous testing and validation protocols to ensure AI outputs are fair, transparent, and compliant with evolving regulations.
Qualifications
- Education: Master’s degree in Computer Science, Artificial Intelligence, or a related field (PhD preferred).
- Experience: Minimum of 5 years of professional experience in AI/ML engineering, with a strong focus on productionizing models.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and distributed computing frameworks (Apache Spark, Ray).
- Cloud Mastery: Extensive experience deploying AI models on AWS, GCP, or Azure using containerization (Docker/Kubernetes).
- Problem Solving: Demonstrated ability to solve complex, ambiguous problems in high-stakes environments.
- Communication: Excellent written and verbal communication skills with the ability to explain complex technical concepts to non-technical stakeholders.