Job Description
Are you ready to architect the future? Nexus Future Labs is leading the charge on The 2026 Initiative, a revolutionary program designed to redefine human-machine interaction through advanced Artificial General Intelligence (AGI). We are looking for visionary Senior AI Architects to build the foundational systems that will power the next decade of innovation.
In this role, you will not just write code; you will define the architecture that bridges current deep learning models with the adaptive, sentient systems envisioned for 2026 and beyond. You will work in a high-performance environment that values radical transparency, intellectual curiosity, and the courage to tackle the impossible.
Why join us?
- Work on the cutting edge of AGI and Neural Symbolic Integration.
- Competitive compensation and equity packages.
- Flexible remote-first culture with premium co-working spaces.
- Access to the latest hardware for Large Language Model training.
Responsibilities
- Design and implement scalable, high-performance AI infrastructure capable of processing petabytes of multimodal data.
- Lead the research and development of novel neural network architectures specifically tailored for the 2026 Horizon roadmap.
- Collaborate with cross-functional teams of cognitive scientists, data engineers, and product designers to translate theoretical research into deployable applications.
- Mentor junior engineers and foster a culture of technical excellence and innovation within the AI division.
- Evaluate and integrate emerging technologies (e.g., neuromorphic computing) to stay ahead of industry trends.
- Ensure the ethical alignment and safety of autonomous systems as they scale.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, or a related field, with a focus on Artificial Intelligence or Machine Learning.
- 7+ years of professional experience in designing complex AI systems, with at least 3 years in a senior leadership or architectural role.
- Expert proficiency in Python, C++, and distributed computing frameworks (e.g., PyTorch, TensorFlow, Apache Spark).
- Deep understanding of Deep Learning, Natural Language Processing (NLP), and Reinforcement Learning.
- Proven track record of delivering production-grade machine learning systems.
- Strong experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies.
- Exceptional problem-solving skills and the ability to thrive in ambiguous, high-pressure environments.