Job Description
Join 2026 Dynamics and help define the technological landscape of the future. We are pioneering breakthroughs in generative AI and autonomous systems, and we are seeking a visionary Senior AI Architect to lead our Project 2026 initiative.
In this role, you will not just implement existing solutions; you will architect the neural frameworks that power the next generation of intelligent applications. You will work in a collaborative, high-performance environment focused on innovation, scalability, and ethical AI development.
Why Join Us?
- Work on cutting-edge technology that defines the future.
- Competitive compensation package and equity options.
- Flexible hybrid work environment in the heart of Austin.
Responsibilities
- Lead R&D Initiatives: Spearhead research into advanced machine learning models, focusing on scalability and real-time inference capabilities for the 2026 ecosystem.
- System Architecture: Design and implement robust, fault-tolerant AI infrastructure, ensuring seamless integration with existing enterprise systems.
- Model Optimization: Continuously refine and optimize deep learning models to reduce latency and improve accuracy under high load.
- Tech Leadership: Mentor a team of junior data scientists and engineers, fostering a culture of technical excellence and continuous learning.
- Cross-Functional Collaboration: Partner with product managers and software engineers to translate complex research into actionable, production-ready features.
- Strategic Roadmapping: Define the technical vision and long-term roadmap for AI capabilities, anticipating future industry trends and technological shifts.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field.
- Experience: 5+ years of professional experience in machine learning engineering, with at least 2 years in a senior leadership or architect role.
- Technical Proficiency: Deep expertise in Python, PyTorch, TensorFlow, or JAX. Strong understanding of distributed computing and MLOps principles.
- Algorithmic Knowledge: Proven track record of designing novel algorithms for Natural Language Processing (NLP) or Computer Vision.
- Cloud Expertise: Hands-on experience with major cloud providers (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Problem Solving: Ability to troubleshoot complex technical challenges and make data-driven architectural decisions.