Job Description
We are pioneering the future. 2026 Systems is looking for a visionary Senior AI Architect to lead our Year 2026 initiative. This is an opportunity to build the foundational infrastructure for tomorrow's intelligent world from the ground up.
In this role, you will bridge the gap between theoretical machine learning breakthroughs and scalable, production-grade software engineering. You will define the architectural standards that will govern our systems for the next decade. If you are passionate about shaping the future of AI and want to work at the intersection of quantum computing and neural networks, we want to hear from you.
Responsibilities
- Lead Architectural Vision: Design and implement the core infrastructure for the Year 2026 initiative, ensuring high scalability, security, and performance.
- ML Pipeline Development: Build and optimize end-to-end machine learning pipelines, from data ingestion to model deployment and monitoring.
- Quantum Integration: Research and prototype integration strategies for quantum computing algorithms into classical ML workflows.
- Technical Mentorship: Guide a team of talented engineers and data scientists, conducting code reviews and fostering a culture of technical excellence.
- Cross-Functional Collaboration: Work closely with product managers, designers, and stakeholders to translate complex technical requirements into robust solutions.
- Compliance & Ethics: Establish and enforce data governance policies and ensure ethical AI practices are maintained throughout the development lifecycle.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, Robotics, or a related technical field.
- Experience: 7+ years of professional experience in software engineering, with at least 3 years in a senior architect or lead machine learning engineering role.
- Core Skills: Deep proficiency in Python, PyTorch, TensorFlow, and modern deep learning frameworks.
- System Design: Strong experience designing distributed systems, microservices architectures, and cloud-native solutions (AWS, GCP, or Azure).
- Tools: Expert knowledge of containerization (Docker/Kubernetes), CI/CD pipelines, and version control (Git).
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders and executive leadership.