Job Description
We are on the precipice of a technological revolution. As we approach 2026, the demand for intelligent, autonomous systems is skyrocketing. Synapse Dynamics is seeking a visionary Senior AI Architect to lead the development of our flagship 'Project 2026' platform—a next-generation agentic AI ecosystem designed to redefine human-machine interaction.
In this high-impact role, you won't just be maintaining legacy models; you will be building the infrastructure for the future. You will work with a world-class team of researchers and engineers to deploy Large Language Models (LLMs) that are not only highly accurate but also deeply autonomous and secure. If you are passionate about pushing the boundaries of Generative AI and want to shape the landscape of technology in 2026, we want to hear from you.
Why Join Us?
- Work on the bleeding edge of AI technology.
- Competitive compensation package with equity.
- Flexible remote-first culture with premium benefits.
Responsibilities
- Architect and implement scalable, fault-tolerant MLOps pipelines designed for 2026 production standards.
- Lead the research and deployment of advanced LLMs, focusing on reasoning, memory, and autonomous agent capabilities.
- Optimize model inference speeds and reduce latency to support real-time applications.
- Collaborate with cross-functional teams to integrate AI solutions into core product ecosystems.
- Establish best practices for AI safety, ethics, and data governance.
- Mentor junior engineers and data scientists, fostering a culture of innovation and technical excellence.
Qualifications
- Master’s degree or PhD in Computer Science, Machine Learning, or a related field.
- 5+ years of professional experience in designing and deploying machine learning systems at scale.
- Deep expertise in Python, PyTorch, or TensorFlow, with a strong command of C++ for performance optimization.
- Proven track record of working with Large Language Models (GPT, LLaMA, etc.) and fine-tuning techniques.
- Experience with distributed systems, Kubernetes, and cloud platforms (AWS/GCP/Azure).
- Strong understanding of prompt engineering and reinforcement learning from human feedback (RLHF).