Job Description
Are you ready to define the technological landscape of 2026? Synthetix Future Systems is seeking a visionary Lead AI Architect to spearhead our next-generation projects. We are not just building software for today; we are engineering the infrastructure for a smarter, autonomous future. In this pivotal role, you will bridge the gap between theoretical AI research and scalable production systems.
You will lead a high-performance team of data scientists and engineers, pushing the boundaries of generative AI, neural interfaces, and predictive modeling. If you thrive in ambiguity and are passionate about solving complex problems that have no existing solutions, we want to hear from you.
Why Join Us?
- Future-Forward Mission: Work on projects directly impacting the roadmap for 2026 and beyond.
- Top-Tier Talent: Collaborate with the brightest minds in the industry.
- Equity Package: Competitive compensation tied to the company's success.
Responsibilities
- Architect and deploy cutting-edge Machine Learning pipelines capable of handling petabyte-scale data.
- Lead the research and implementation of next-generation neural network architectures for real-time decision making.
- Mentor senior engineers and junior developers, fostering a culture of innovation and technical excellence.
- Define technical strategy for the 2026 roadmap, ensuring scalability, security, and efficiency.
- Collaborate with product management to translate abstract futuristic concepts into tangible product features.
- Optimize existing models for edge computing environments and distributed systems.
- Conduct rigorous code reviews and drive architectural standardization across the organization.
Qualifications
- Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- 10+ years of experience in software engineering with a strong focus on Machine Learning and AI.
- Deep expertise in Python, C++, and modern deep learning frameworks (TensorFlow, PyTorch).
- Proven track record of leading high-impact engineering teams and managing large-scale projects.
- Strong understanding of NLP, Computer Vision, or Reinforcement Learning.
- Experience with cloud infrastructure (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Excellent communication skills with the ability to articulate complex technical concepts to non-technical stakeholders.