Job Description
Are you ready to architect the future? Apex Horizon Systems is at the forefront of the 2026 technological revolution, developing next-generation Artificial General Intelligence (AGI) frameworks. We are seeking a visionary Lead AI Architect to lead our engineering division in designing scalable, ethical, and high-performance systems that will define the digital ecosystem of tomorrow.
In this role, you won't just write code; you will define the paradigms of machine learning for the coming decade. You will work directly with our CTO and a team of elite researchers to bridge the gap between theoretical AI and production-grade infrastructure. If you thrive in ambiguity and are driven by the challenge of solving the unsolvable, this is your opportunity to leave a lasting legacy.
Why Join Us?
- Work on projects that will be foundational to the 2026 tech landscape.
- Competitive equity package and top-tier healthcare.
- Flexible remote-first culture with quarterly innovation retreats.
- Access to cutting-edge compute resources and proprietary datasets.
Responsibilities
- Architect and design the core neural network infrastructure for our proprietary LLM and reinforcement learning engines.
- Lead a high-performance team of ML engineers and data scientists, fostering a culture of technical excellence and rapid prototyping.
- Optimize model inference latency and reduce computational costs by 40% using novel quantization techniques.
- Define the technical roadmap for AI safety, interpretability, and compliance with emerging 2026 regulatory standards.
- Collaborate with product teams to translate complex research into consumer-facing features.
- Implement rigorous testing protocols and CI/CD pipelines for machine learning models.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, or a related field with a focus on AI/ML.
- 10+ years of experience in software engineering, with at least 5 years in leading AI/ML architecture roles.
- Deep expertise in Deep Learning frameworks (PyTorch, TensorFlow, JAX) and high-performance computing.
- Proven track record of deploying large-scale models into production environments.
- Strong understanding of distributed systems, cloud architecture (AWS/GCP), and Kubernetes.
- Experience with NLP, Computer Vision, or Multi-modal AI systems is highly preferred.