Job Description
Are you ready to architect the intelligent systems of tomorrow? Apex Horizon Technologies is seeking a visionary Lead AI Architect (2026 Vision) to define the next generation of artificial intelligence. In this pivotal role, you will bridge the gap between theoretical breakthroughs and scalable production systems, ensuring our AI infrastructure remains at the forefront of innovation.
We are not just building software; we are engineering the future. You will lead a high-performing team of data scientists and engineers, guiding them through complex challenges in Large Language Models (LLMs), predictive analytics, and autonomous agents.
Why Join Us?
- Impact: Shape the roadmap for AI adoption in enterprise sectors.
- Compensation: Competitive salary and equity package.
- Environment: Work in a state-of-the-art facility in the heart of San Francisco.
Responsibilities
- Architectural Leadership: Design and oversee the development of scalable AI/ML infrastructure, ensuring high availability and performance.
- Model Strategy: Define the technical strategy for deploying Generative AI and LLMs into production environments.
- Team Mentorship: Lead, mentor, and coach a team of engineers and data scientists, fostering a culture of technical excellence and innovation.
- R&D Oversight: Stay ahead of the curve on emerging AI trends (e.g., Quantum AI, Neuromorphic computing) and integrate relevant technologies.
- Cross-Functional Collaboration: Partner with product managers and stakeholders to translate business requirements into robust technical solutions.
- Performance Optimization: Continuously monitor and optimize model accuracy, latency, and cost-efficiency.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related technical field.
- Experience: 7+ years of experience in software engineering, with at least 3 years in a Lead or Architect role within the AI/ML space.
- Technical Skills: Deep expertise in Python, PyTorch, TensorFlow, and MLOps platforms (e.g., Kubeflow, MLflow).
- AI Proficiency: Proven experience with LLMs, fine-tuning, RAG (Retrieval-Augmented Generation), and NLP.
- Cloud Mastery: Strong proficiency in cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Problem Solving: Exceptional ability to solve complex, unstructured problems and design resilient systems.