Job Description
We are not just looking for the present; we are building the infrastructure for 2026 and beyond. Nexus Horizon Labs is at the forefront of the Autonomous Intelligence revolution, seeking a visionary Lead AI Architect to spearhead the development of next-generation neural networks and autonomous systems. If you thrive in a high-performance environment and want to define the trajectory of artificial intelligence, we want to meet you.
As a key leader in our Engineering division, you will bridge the gap between theoretical research and scalable production systems, ensuring our solutions are robust, ethical, and future-proof.
Why Join Us?
- Work on cutting-edge projects that redefine human-machine interaction.
- Competitive compensation package and equity options.
- Flexible remote-first culture with premium office amenities in SOMA.
Responsibilities
- Architect Scalable Systems: Design and implement robust, scalable AI architectures capable of handling petabyte-scale data and high-frequency inference.
- Lead the 2026 Roadmap: Define the technical strategy for our autonomous agent ecosystem, aligning short-term milestones with long-term 2026 goals.
- Model Optimization: Spearhead research into model compression, quantization, and edge-deployment strategies to ensure real-time performance.
- Technical Mentorship: Mentor senior engineers and data scientists, fostering a culture of continuous learning and innovation.
- Cross-Functional Collaboration: Partner with product managers, security experts, and researchers to translate complex requirements into technical blueprints.
- Compliance & Ethics: Establish governance frameworks for AI safety and bias mitigation in all deployed models.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related field.
- Experience: 8+ years of professional experience in machine learning engineering, with at least 3 years in a leadership or architectural role.
- Technical Stack: Deep proficiency in Python, PyTorch, TensorFlow, and distributed computing frameworks (Kubernetes, Docker).
- Domain Knowledge: Proven experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Reinforcement Learning.
- System Design: Strong understanding of cloud infrastructure (AWS, GCP) and high-availability system design patterns.
- Communication: Exceptional ability to communicate complex technical concepts to diverse stakeholders.