Job Description
Are you ready to define the technological landscape of the future?
Nexus 2026 Technologies is seeking a visionary Lead AI Architect to spearhead our R&D division. We are pioneering the advanced AI systems, neural architectures, and quantum-ready interfaces that will define the world in the year 2026 and beyond.
In this role, you will not just build software; you will architect the cognitive backbone of the next generation of human-computer interaction. We are looking for a thought leader who thrives on ambiguity and possesses the technical prowess to turn sci-fi concepts into production-ready reality.
Why Join Us?
• Be at the forefront of the AI revolution.
• Work with state-of-the-art hardware and software stacks.
• Competitive equity and benefits packages.
• Remote-first culture with a San Francisco core.
Responsibilities
- Architect Next-Gen AI Systems: Design and implement scalable machine learning infrastructure capable of handling petabyte-scale datasets with zero-latency inference.
- Research & Development: Lead the exploration of novel neural network architectures, focusing on Generative AI, Large Language Models (LLMs), and Reinforcement Learning.
- Quantum Integration: Collaborate with quantum computing teams to develop hybrid algorithms that leverage the power of future computing paradigms.
- Ethical AI Implementation: Establish and enforce rigorous safety guidelines and bias mitigation strategies to ensure responsible AI deployment.
- Team Leadership: Mentor a team of senior engineers and data scientists, fostering a culture of innovation, continuous learning, and high performance.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Mathematics, or a related field with a focus on Artificial Intelligence.
- Experience: Minimum of 6 years of professional experience in AI/ML engineering, with at least 2 years in a lead or architect role.
- Technical Skills: Deep expertise in Python, PyTorch, TensorFlow, and modern distributed computing frameworks (e.g., Apache Spark, Kubernetes).
- Domain Knowledge: Proven track record of publishing in top-tier AI conferences (NeurIPS, ICML, CVPR) or shipping high-impact production models.
- Soft Skills: Exceptional communication skills with the ability to translate complex technical concepts for diverse stakeholders.