Job Description
Join Nexus Futura at the forefront of technological evolution as we build the AI-driven solutions that will define 2026. We're seeking visionary AI Solutions Architects to architect, develop, and deploy cutting-edge machine learning systems that will transform industries. You'll work in our state-of-the-art San Francisco headquarters, collaborating with Nobel laureates and industry pioneers to solve humanity's most complex challenges. This role offers unparalleled growth opportunities in quantum computing integration, neural network optimization, and ethical AI frameworks.
Our comprehensive benefits package includes equity grants, unlimited learning stipends, and flexible hybrid work arrangements. We're not just building the future – we're creating the blueprint for how humanity and AI will coexist in 2026 and beyond.
Responsibilities
- Design and implement scalable AI infrastructure for enterprise clients across healthcare, finance, and logistics sectors
- Lead cross-functional teams in developing ethical AI frameworks aligned with 2026 regulatory standards
- Architect hybrid quantum-classical computing solutions for next-generation ML models
- Optimize neural network architectures for edge computing deployment in IoT ecosystems
- Conduct advanced research in federated learning and differential privacy techniques
- Develop AI governance frameworks for autonomous system decision-making processes
- Mentor junior engineers in emerging AI paradigms and implementation best practices
Qualifications
- PhD in Computer Science, Mathematics, or related field with 5+ years of AI/ML architecture experience
- Proven expertise in deploying production-level LLMs with >100M parameters
- Deep understanding of quantum computing principles and quantum machine learning algorithms
- Strong background in federated learning frameworks and distributed ML systems
- Certification in AI ethics (e.g., IEEE 7000™, EU AI Act compliance)
- Experience with MLOps tools (MLflow, Kubeflow) and cloud-native AI deployment
- Published research in top-tier AI conferences (NeurIPS, ICML, ICLR) or equivalent industry impact