Job Description
We are building the systems that will define the technological landscape of 2026 and beyond. Synapse Future Labs is seeking a visionary Principal AI Architect to lead our core research and infrastructure initiatives.
In this role, you will bridge the gap between theoretical AI research and production-grade engineering. You will architect the scalable frameworks necessary for next-generation autonomous systems, ensuring our solutions are not just functional, but revolutionary. If you are obsessed with the future of Machine Learning, Large Language Models (LLMs), and AGI (Artificial General Intelligence), this is your calling.
Why Join Us?
- Impact: Work on projects that will scale to billions of users.
- Rewards: Top-tier compensation package and equity opportunities.
- Culture: A diverse, elite team of engineers and researchers from top-tier tech firms.
Responsibilities
- Architect Future-Proof Systems: Design and oversee the implementation of robust, scalable AI infrastructure capable of handling the demands of 2026.
- Roadmap Leadership: Define the technical roadmap for our 2026 vision, translating abstract research goals into concrete engineering milestones.
- Model Optimization: Lead efforts in fine-tuning and optimizing large-scale models for latency, memory efficiency, and throughput.
- Technical Mentorship: Mentor senior engineers and researchers, fostering a culture of technical excellence and innovation.
- Cross-Functional Collaboration: Partner with product and engineering teams to integrate AI capabilities seamlessly into consumer products.
- Research & Development: Stay at the forefront of AI trends, evaluating new technologies to drive competitive advantage.
Qualifications
- Experience: 8+ years of experience in software engineering or machine learning, with at least 3 years in a senior architecture or principal role.
- Core Tech: Deep expertise in Python, PyTorch, or TensorFlow, with proven experience deploying models at scale.
- System Design: Strong background in distributed systems, cloud architecture (AWS/GCP), and high-availability solutions.
- Education: BS, MS, or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- Leadership: Demonstrated ability to lead high-performance engineering teams and influence technical strategy.
- Problem Solving: Exceptional analytical skills with a track record of solving complex, ambiguous problems.