Job Description
Are you ready to architect the future of intelligence?
Apex Horizon Systems is pioneering the next frontier of technology. We are seeking a visionary Lead Futurist AI Engineer to spearhead our initiatives for the year 2026 and beyond. If you possess an insatiable curiosity for Artificial General Intelligence (AGI), autonomous systems, and ethical machine learning, we want to hear from you.
As part of our elite R&D division, you will not just be writing code; you will be defining the paradigms of synthetic cognition. We operate at the intersection of quantum computing and neural networks, pushing the boundaries of what is possible.
Why Join Us?
- Work on projects that will define the next decade of human evolution.
- Competitive compensation package including equity options.
- Access to state-of-the-art hardware and research facilities.
- Flexible, remote-first culture with a focus on autonomy.
Responsibilities
- Architect and deploy scalable, self-improving AI models capable of handling complex, multi-modal data streams in real-time.
- Lead the research and development of AGI frameworks, focusing on reasoning, planning, and adaptive learning algorithms.
- Establish ethical guidelines and safety protocols for autonomous systems to ensure responsible deployment.
- Collaborate with cross-functional teams of quantum physicists, data scientists, and UX designers to integrate AI seamlessly into consumer products.
- Mentor junior engineers and researchers, fostering a culture of innovation and continuous learning.
- Conduct rigorous performance testing and optimization of neural networks running on next-generation hardware.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.
- Extensive experience with deep learning frameworks (PyTorch, TensorFlow, JAX) and large language model fine-tuning.
- Strong proficiency in Python, C++, and GPU acceleration libraries (CUDA, cuDNN).
- Demonstrated experience in implementing reinforcement learning strategies for decision-making systems.
- Deep understanding of transformer architectures and attention mechanisms.
- Excellent problem-solving skills and the ability to thrive in high-pressure, fast-paced environments.
- Experience with quantum computing libraries or simulators is a strong plus.