Job Description
We are building the infrastructure for the future. Apex Horizon Systems is at the forefront of next-generation artificial intelligence, and we are looking for a visionary Lead AI Architect to help define our roadmap through 2026 and beyond.
The Role
In this pivotal role, you will bridge the gap between theoretical research and scalable production engineering. You won't just be maintaining models; you will be architecting the cognitive architecture that will power autonomous agents, predictive analytics, and generative interfaces in a post-2026 world. You will work in a high-velocity environment where technical excellence meets bold innovation.
Key Responsibilities
- Architect the Future: Design and oversee the deployment of large-scale neural networks and generative AI models capable of handling complex, real-time decision-making.
- Technical Leadership: Mentor a world-class team of ML engineers and data scientists, fostering a culture of curiosity and technical rigor.
- System Optimization: Implement advanced optimization techniques to reduce latency and improve inference efficiency on edge devices and cloud infrastructure.
- Strategic Roadmap: Collaborate with product and research teams to define technical milestones for our 2026 product suite.
- Ethical AI: Establish and enforce guidelines for responsible AI development, ensuring bias mitigation and data privacy compliance.
Qualifications
- Education: MS or PhD in Computer Science, Machine Learning, or a related quantitative field.
- Experience: 8+ years of experience in software engineering with at least 4 years dedicated to AI/ML architecture.
- Core Tech: Deep expertise in PyTorch, TensorFlow, or JAX; experience with LLMs (Large Language Models) and transformers.
- Infrastructure: Strong background in distributed systems, cloud architecture (AWS/Azure/GCP), and MLOps pipelines.
- Problem Solving: Proven track record of solving complex, ambiguous problems in high-stakes environments.
Responsibilities
- Design and implement scalable AI architectures for enterprise applications.
- Lead code reviews and architecture reviews to ensure technical debt is minimized.
- Translate research papers into production-ready code and infrastructure.
- Manage budget and resource allocation for technical projects.
- Stay ahead of the curve on emerging AI trends and technologies.
Qualifications
- Master’s degree or PhD in Computer Science, AI, or related field.
- Extensive experience with Python, C++, and GPU acceleration.
- Strong understanding of deep learning theory and neural network optimization.
- Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.
- Experience with containerization and orchestration (Docker, Kubernetes).