Job Description
We are looking for a visionary Lead AI Architect to shape the trajectory of our technology in 2026 and beyond. At Nexus Horizon AI, we are building the infrastructure for the next generation of Artificial General Intelligence. You will be at the forefront of research, designing scalable systems that bridge the gap between theoretical models and real-world applications. If you are passionate about the future of AI and want to lead a team of world-class engineers, this is your opportunity.
Why Join Us?
- Work on cutting-edge projects that define the future of human-computer interaction.
- Competitive compensation and equity packages.
- Flexible remote-first culture with a hub in San Francisco.
Responsibilities
- System Architecture: Design and implement high-performance, scalable AI infrastructure capable of supporting large-scale model training and inference.
- Research Leadership: Spearhead research initiatives into efficient transformer architectures and novel neural network paradigms.
- Model Optimization: Oversee the optimization of models for latency, throughput, and memory efficiency on diverse hardware accelerators.
- Team Mentorship: Guide and mentor senior engineers and data scientists, fostering a culture of technical excellence and innovation.
- Strategic Planning: Translate business requirements into technical roadmaps, ensuring alignment with the 2026 product vision.
- Cross-Functional Collaboration: Partner with product managers, researchers, and designers to deliver integrated AI solutions.
Qualifications
- Education: Master’s or PhD in Computer Science, Machine Learning, or a related technical field.
- Experience: 7+ years of experience in software engineering, with at least 4 years specifically focused on AI/ML system design.
- Technical Skills: Deep expertise in Python, PyTorch, or TensorFlow; experience with distributed training frameworks.
- Specialization: Strong background in Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning.
- Infrastructure: Proficiency in cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes).
- Problem Solving: Proven track record of solving complex engineering challenges in high-stakes environments.