Job Description
The Opportunity
Are you ready to architect the artificial intelligence systems that will define the landscape of 2026 and beyond? Nexus Future Labs is seeking a visionary Future AI Architect to lead our next-generation research division. In this role, you won't just implement existing models; you will design the foundational architectures for sentient computing, ethical AI, and hyper-personalized digital experiences.
We are looking for a pioneer who thrives in ambiguity and possesses the technical prowess to turn sci-fi concepts into scalable reality. If you are passionate about the future of technology and want to build the tools that will reshape humanity's interaction with machines, this is your chance to lead.
Why Join Us?
- Work on cutting-edge projects with a team of world-class researchers.
- Competitive compensation package with equity options.
- Flexible remote-first policy with quarterly in-person innovation sprints in San Francisco.
Responsibilities
- Design and implement scalable, high-performance AI architectures capable of processing petabytes of real-time data.
- Lead research initiatives focused on Generative AI, Large Language Models (LLMs), and autonomous decision-making systems.
- Collaborate with cross-functional teams to integrate AI solutions into consumer and enterprise products.
- Establish best practices for model training, evaluation, and ethical AI deployment.
- Mentor junior engineers and data scientists, fostering a culture of continuous learning and innovation.
- Stay at the forefront of industry trends, evaluating emerging technologies (e.g., Quantum AI, Neuromorphic Computing) for potential integration.
- Document architectural decisions and contribute to the company’s technical knowledge base.
Qualifications
- Master’s or PhD in Computer Science, Artificial Intelligence, or a related field from a top-tier institution.
- Minimum of 5 years of experience in software engineering and machine learning, with at least 2 years in a lead or architect role.
- Deep expertise in Python, PyTorch, TensorFlow, and C++.
- Strong understanding of statistical learning, natural language processing, and computer vision.
- Proven track record of publishing research papers in top-tier conferences (NeurIPS, ICML, ICLR).
- Excellent problem-solving skills with the ability to translate complex business requirements into technical specifications.
- Experience with cloud infrastructure (AWS, GCP, or Azure) and MLOps pipelines.