Job Description
We are building the infrastructure for tomorrow, today. As a Future-Ready AI Architect, you will lead the technical strategy for deploying autonomous agents and generative AI systems that define the landscape of 2026 and beyond. We are seeking a visionary engineer who doesn't just adapt to the future, but helps shape it.
Why Join Us?
- Work on cutting-edge projects in Spatial Computing and Quantum-adjacent algorithms.
- Competitive compensation and equity packages.
- Flexible remote-first culture with hubs in San Francisco and Austin.
In this role, you will be responsible for architecting scalable, secure, and high-performance machine learning infrastructures that handle petabyte-scale data with real-time precision.
Responsibilities
- Design Next-Gen Architectures: Design and implement neural network architectures optimized for edge computing, distributed systems, and low-latency environments.
- Generative AI Integration: Lead the integration of Large Language Models (LLMs) and multimodal AI into core product workflows to enhance user experiences.
- MLOps Excellence: Establish robust MLOps pipelines, ensuring automated testing, deployment, and monitoring of production models.
- Ethical AI Leadership: Define and enforce best practices for data governance, bias mitigation, and responsible AI deployment.
- Talent Development: Mentor a team of junior data scientists and backend engineers, fostering a culture of continuous innovation.
- Strategic Planning: Collaborate with product and executive leadership to translate futuristic tech concepts into actionable engineering roadmaps.
Qualifications
- Experience: 7+ years in software engineering and machine learning, with at least 3 years in a lead architecture or senior engineering role.
- Core Tech Stack: Deep expertise in Python, PyTorch, and TensorFlow; experience with Rust or Go is a plus.
- Cloud & Infrastructure: Proficiency in AWS, GCP, or Azure, with strong experience using Docker, Kubernetes, and Terraform.
- Future-Ready Skills: Demonstrated experience in 2026-era technologies such as Spatial Web (WebXR), Federated Learning, or AI agents.
- Problem Solving: Strong ability to solve complex scalability and performance bottlenecks in high-traffic environments.
- Education: MS or PhD in Computer Science, Artificial Intelligence, or a related technical field.