Job Description
Welcome to the vanguard of technological evolution. We are seeking a Senior Synthetic Intelligence Systems Architect to lead our R&D division in San Francisco. As we approach the 2026 paradigm shift in machine autonomy, you will be responsible for architecting the next generation of self-evolving neural networks and synthetic data ecosystems.
In this pivotal role, you will bridge the gap between theoretical AI research and scalable production systems, ensuring our platforms are not just smart, but future-proof.
Why Join Us?
- Work at the intersection of Quantum Computing and Generative AI.
- Shape the ethical frameworks governing autonomous systems.
- Competitive compensation package and equity in a unicorn startup.
Key Responsibilities:
- Architect and deploy high-performance synthetic intelligence models capable of autonomous decision-making.
- Design robust data pipelines for real-time synthetic data generation and training.
- Collaborate with cross-functional teams to integrate AI systems into legacy and next-gen infrastructure.
- Establish governance frameworks for AI ethics, safety, and compliance in the 2026 landscape.
- Mentor junior engineers and guide research initiatives in neural architecture search (NAS).
- Optimize system latency and computational efficiency for edge deployment.
Qualifications:
- Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- 10+ years of experience in software engineering, with at least 5 years in AI/ML architecture.
- Deep expertise in deep learning frameworks (PyTorch, TensorFlow) and distributed computing systems.
- Proven track record of leading complex technical projects from conception to production.
- Strong understanding of AI safety, bias mitigation, and regulatory compliance.
- Excellent communication skills with the ability to articulate complex technical concepts to diverse stakeholders.
Responsibilities
- Architect and deploy high-performance synthetic intelligence models capable of autonomous decision-making.
- Design robust data pipelines for real-time synthetic data generation and training.
- Collaborate with cross-functional teams to integrate AI systems into legacy and next-gen infrastructure.
- Establish governance frameworks for AI ethics, safety, and compliance in the 2026 landscape.
- Mentor junior engineers and guide research initiatives in neural architecture search (NAS).
- Optimize system latency and computational efficiency for edge deployment.
Qualifications
- Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- 10+ years of experience in software engineering, with at least 5 years in AI/ML architecture.
- Deep expertise in deep learning frameworks (PyTorch, TensorFlow) and distributed computing systems.
- Proven track record of leading complex technical projects from conception to production.
- Strong understanding of AI safety, bias mitigation, and regulatory compliance.
- Excellent communication skills with the ability to articulate complex technical concepts to diverse stakeholders.