Job Description
Are you ready to define the architecture of the future? Apex Innovation Systems is seeking a visionary Lead AI Architect to spearhead our next-generation machine learning initiatives. In this role, you won't just build models; you will architect the intelligent systems that will dominate the landscape of 2026 and beyond.
We are a pioneer in generative AI and autonomous agents. We need a leader who understands the nuances of large-scale neural networks and the ethical implications of advanced artificial intelligence. If you are passionate about solving complex problems and shaping the digital frontier, we want to hear from you.
Responsibilities
- Design and oversee the end-to-end architecture for scalable, high-performance AI solutions.
- Define the technical roadmap for AI capabilities leading up to the 2026 product launch and beyond.
- Lead a high-performing team of data scientists, ML engineers, and researchers.
- Collaborate closely with product managers and stakeholders to translate complex business needs into technical algorithms.
- Ensure model accuracy, fairness, robustness, and explainability across all deployment environments.
- Stay ahead of the curve in emerging AI paradigms, including LLMs and reinforcement learning.
- Drive the adoption of MLOps best practices to ensure seamless model deployment and monitoring.
Qualifications
- PhD or Master’s degree in Computer Science, Machine Learning, Statistics, or a related quantitative field.
- 10+ years of experience in AI/ML engineering, with at least 3 years in a leadership or architectural role.
- Expert proficiency in Python, PyTorch, TensorFlow, and modern deep learning frameworks.
- Deep understanding of MLOps, cloud infrastructure (AWS/GCP/Azure), and containerization technologies (Docker/Kubernetes).
- Strong grasp of Generative AI models, Large Language Models (LLMs), and transformer architectures.
- Proven track record of shipping production-grade AI products that have a measurable business impact.
- Excellent communication skills with the ability to bridge the gap between technical and non-technical audiences.