Job Description
Are you ready to architect the future of intelligence?
Synthetix Future Labs is seeking a visionary Lead AI Architect to spearhead our 2026 Horizon Initiative. In this pivotal role, you will define the architectural paradigms that will power the next generation of autonomous systems and quantum-enhanced machine learning. We are not just building software for today; we are engineering the breakthroughs required for tomorrow.
You will be at the forefront of the AI revolution, collaborating with world-class researchers and engineers to push the boundaries of what is possible in neural architectures and cognitive computing.
Why Join Us?
- Work on cutting-edge technology that will define the industry in 2026 and beyond.
- Competitive compensation package and equity opportunities in a high-growth startup.
- Flexible remote-first culture with hubs in San Francisco and New York.
Responsibilities
- Design and implement scalable, next-generation neural network architectures tailored for the 2026 computing landscape.
- Lead a team of senior engineers and researchers to innovate on unsolved problems in Natural Language Processing and Computer Vision.
- Translate theoretical research into production-ready code with a focus on efficiency, accuracy, and real-time processing.
- Mentor junior and mid-level engineers, fostering a culture of continuous learning and technical excellence.
- Collaborate with product stakeholders to define technical roadmaps that align with long-term business goals.
- Stay ahead of industry trends, specifically regarding quantum computing integration and edge AI deployment.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, or a related technical field (or equivalent professional experience).
- Minimum of 5+ years of experience in machine learning engineering, with at least 2 years in a leadership or architect role.
- Deep proficiency in Python, PyTorch, TensorFlow, and distributed computing frameworks.
- Proven track record of publishing in top-tier AI conferences (NeurIPS, ICML, ICLR) or contributing to high-impact open-source projects.
- Strong understanding of optimization techniques, large language models, and reinforcement learning algorithms.
- Excellent communication skills with the ability to articulate complex technical concepts to non-technical stakeholders.