Job Description
Are you ready to define the next era of artificial intelligence? Nexus Horizon Labs is pioneering the technologies that will power the world in 2026 and beyond. We are seeking a visionary Senior AI Architect to lead our cutting-edge research in Generative AI, Large Language Models (LLMs), and autonomous agents.
In this pivotal role, you will not just build models; you will architect the ethical framework and scalable infrastructure required to deploy AI systems at a global scale. If you are passionate about the future of technology and want to solve the most complex challenges in machine learning, we want to hear from you.
Why Join Us?
We offer a competitive compensation package, fully remote-first culture (with hubs in SF), and the opportunity to work on projects that will shape the trajectory of human-computer interaction.
Responsibilities
- Architect & Deploy: Design and implement robust, scalable AI infrastructure using Python, PyTorch, and cloud-native services (AWS/Azure/GCP).
- Model Optimization: Lead initiatives to optimize LLM inference speeds and reduce latency for real-time applications.
- R&D Leadership: Drive research in next-generation AI paradigms, including multimodal learning and reinforcement learning.
- Ethical AI: Establish and enforce governance frameworks to ensure AI outputs are fair, transparent, and safe.
- Cross-Functional Collaboration: Partner with product, engineering, and legal teams to translate technical capabilities into market-ready solutions.
- Mentorship: Mentor junior engineers and data scientists, fostering a culture of innovation and continuous learning.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related field.
- Experience: 5+ years of professional experience in AI/ML engineering, with at least 2 years in a leadership or senior architect role.
- Technical Skills: Deep expertise in Machine Learning, Deep Learning, and Natural Language Processing (NLP).
- Programming: Proficiency in Python, C++, and experience with major ML frameworks (TensorFlow, PyTorch, JAX).
- Tools: Experience with MLOps tools (Docker, Kubernetes, MLflow) and cloud platforms.
- Problem Solving: Proven track record of solving complex engineering problems and delivering high-impact projects.