Job Description
Join the Vanguard of Artificial Intelligence
Nexus Horizon Labs is on a mission to redefine the technological landscape by 2026. We are seeking a visionary Senior AI Architect to lead the development of our next-generation autonomous systems and large-scale generative models. If you are passionate about pushing the boundaries of what is possible in AI and want to leave a legacy in the industry, this is your opportunity.
As a key member of our core engineering team, you will bridge the gap between theoretical research and scalable production systems. We are not just building tools for today; we are architecting the infrastructure for tomorrow.
Why Join Us?
- Work on cutting-edge projects that define the future of technology.
- Competitive salary and equity package.
- Flexible remote-first culture with premium office amenities in SF.
- Continuous learning opportunities with industry leaders.
Responsibilities
- Architect Scalable Systems: Design and implement robust, high-performance AI infrastructures capable of handling petabyte-scale data and millions of concurrent requests.
- Lead the 2026 Roadmap: Collaborate with C-suite executives and product leads to define the technical strategy and roadmap for our upcoming AI releases.
- Model Optimization: Drive research and engineering initiatives to optimize model inference times and reduce operational costs using advanced quantization and pruning techniques.
- Mentorship: Cultivate a high-performing engineering culture by mentoring junior architects and data scientists, conducting code reviews, and establishing best practices.
- Ethical AI Governance: Ensure all deployed models adhere to strict ethical guidelines and safety standards, mitigating bias and ensuring fairness in automated decision-making processes.
Qualifications
- Education: Master’s or PhD in Computer Science, Machine Learning, or a related quantitative field from a top-tier institution.
- Experience: 5+ years of professional experience in building and deploying large-scale machine learning models; experience leading engineering teams is a strong plus.
- Technical Stack: Deep proficiency in Python, PyTorch, TensorFlow, and experience with MLOps tools (Kubeflow, MLflow, Airflow).
- Cloud Expertise: Extensive experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Critical Thinking: Ability to translate complex business requirements into elegant, technical solutions and handle ambiguity in fast-paced environments.