Job Description
Are you ready to define the architecture of tomorrow?
Apex Future Labs is pioneering the 2026 Horizon Initiative, a cutting-edge research program dedicated to building the next generation of autonomous intelligence systems. We are seeking a visionary Senior AI Architect to lead our technical strategy and oversee the development of scalable, resilient, and revolutionary AI infrastructures.
In this pivotal role, you won't just maintain existing systems; you will architect the future. You will work at the intersection of Deep Learning, Quantum Computing interfaces, and Edge Intelligence. Join a team of elite engineers and scientists committed to pushing the boundaries of what is possible.
Why join us?
- Work on mission-critical projects with a $50M R&D budget.
- Competitive equity package and full benefits.
- Flexible remote-first culture with quarterly innovation sprints.
Responsibilities
- Lead Architectural Strategy: Design and oversee the end-to-end technical architecture for the 2026 Horizon AI ecosystem, ensuring scalability and high-performance computing capabilities.
- R&D Leadership: Drive research initiatives to integrate emerging technologies, such as Neuromorphic computing and Large Language Models (LLMs), into our core infrastructure.
- System Optimization: Analyze system bottlenecks and implement high-performance solutions to optimize model training and inference latency.
- Talent Mentorship: Mentor a team of senior data scientists and machine learning engineers, fostering a culture of technical excellence and continuous learning.
- Cross-Functional Collaboration: Partner with product managers and security experts to align technical roadmaps with business objectives and compliance standards.
- Technical Governance: Establish coding standards, architectural patterns, and CI/CD pipelines to ensure robust software delivery.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Mathematics, or a related field, with a focus on Artificial Intelligence or Machine Learning.
- Experience: 8+ years of experience in software engineering and machine learning architecture, with at least 3 years in a senior leadership role.
- Technical Stack: Expert proficiency in Python, C++, Rust, and frameworks such as TensorFlow, PyTorch, or JAX.
- Distributed Systems: Proven experience designing distributed systems that handle high concurrency and massive data throughput.
- Cloud Mastery: Deep knowledge of cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Innovation: Demonstrated track record of publishing patents or leading open-source contributions in the AI space.