Job Description
Are you ready to architect the future of intelligent systems?
Apex Future Systems is pioneering the The 2026 Horizon Initiative—a groundbreaking research and development program designed to redefine the boundaries of Artificial General Intelligence (AGI) and predictive analytics. We are looking for a visionary Lead AI Architect to lead our elite engineering team in San Francisco.
In this role, you will not just write code; you will define the roadmap for the next decade of technology. You will build scalable, fault-tolerant neural architectures capable of processing exabytes of data in real-time. If you are passionate about solving complex problems at the intersection of deep learning, distributed systems, and ethical AI, this is your opportunity to leave a legacy.
Why join The 2026 Horizon?
- Work on state-of-the-art models that will power the global economy in the future.
- Competitive compensation package including equity and performance bonuses.
- Flexible remote-first policy with a premium office in the heart of SOMA.
Responsibilities
- Define the 2026 Vision: Lead the architectural strategy for our flagship AI initiatives, ensuring scalability and long-term viability.
- Model Development: Spearhead the design and implementation of cutting-edge deep learning models, including Transformers and diffusion architectures.
- System Optimization: Architect high-performance computing clusters to reduce latency and increase inference speed by 200%.
- Team Leadership: Mentor a team of senior data scientists and engineers, fostering a culture of innovation and technical excellence.
- Roadmap Planning: Collaborate with product leadership to translate business requirements into technical roadmaps for the 2026 release cycle.
- Security & Compliance: Implement rigorous security protocols to ensure data privacy and ethical AI usage.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related field (or equivalent practical experience).
- Experience: 8+ years of experience in machine learning, deep learning, or artificial intelligence engineering.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and experience with large-scale distributed systems (Kubernetes, AWS/GCP).
- Leadership: Demonstrated history of leading high-performing engineering teams and managing complex projects.
- Innovation: Proven track record of publishing research papers or delivering breakthrough AI products.
- Problem Solving: Exceptional ability to debug complex system failures and optimize performance bottlenecks.