Job Description
Are you ready to build the future?
Synapse Future is seeking a visionary Senior AI Architect (2026 Vision) to lead the development of next-generation artificial intelligence systems. As we look toward the technological horizon of 2026, we need a leader who can bridge the gap between theoretical breakthroughs and scalable production engineering. This is a unique opportunity to define the architectural standards for the AI infrastructure of tomorrow.
In this role, you will not just maintain existing systems; you will architect the core components of our upcoming Neural-Quantum integration platform. If you are passionate about Large Language Models (LLMs), Generative AI, and the ethical implications of future tech, we want to hear from you.
Why Join Us?
- Future-Proof Your Career: Work on technologies that will define the 2026 landscape.
- Competitive Compensation: Base salary of $180k-$260k plus performance bonuses.
- Equity Package: Significant stock options in a high-growth unicorn.
- Flexible Work: Hybrid model based in the heart of San Francisco.
Responsibilities
- Design and implement scalable, high-performance AI architectures for enterprise-grade applications.
- Lead the research and integration of emerging AI paradigms, specifically focusing on Generative Adversarial Networks (GANs) and Transformer models.
- Collaborate with cross-functional teams to translate complex business requirements into robust AI technical solutions.
- Mentor junior engineers and data scientists, fostering a culture of continuous learning and innovation.
- Ensure system reliability, security, and ethical AI compliance across all deployed models.
- Optimize existing neural networks for reduced latency and improved inference speeds.
- Stay ahead of industry trends to recommend new technologies that provide a competitive advantage.
Qualifications
- Master’s degree or PhD in Computer Science, Mathematics, or a related technical field (or equivalent professional experience).
- Minimum of 8+ years of experience in software engineering, with at least 5 years focused specifically on Artificial Intelligence and Machine Learning.
- Deep expertise in Python, C++, and TensorFlow or PyTorch.
- Proven experience in designing Large Language Models (LLMs) and Natural Language Processing (NLP) pipelines.
- Strong understanding of cloud infrastructure (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Excellent problem-solving skills and the ability to work in a fast-paced, agile environment.
- Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.