Job Description
We are building the future. Join 2026 Innovations as a Senior AI Infrastructure Architect and help define the technological landscape for the next decade. Our mission is to deploy next-generation Artificial Intelligence systems that are scalable, secure, and transformative for enterprise clients.
In this pivotal role, you will bridge the gap between theoretical machine learning research and production-grade infrastructure. You will be responsible for the architecture, development, and deployment of our core AI models, ensuring they perform efficiently at scale.
Why You'll Love It Here:
- Work on cutting-edge Generative AI and Large Language Model (LLM) deployments.
- Competitive compensation package including equity.
- Flexible remote-first culture with headquarters in San Francisco.
Responsibilities
- Design and implement scalable, high-performance AI infrastructure pipelines using Python, PyTorch, and TensorFlow.
- Lead the architecture and optimization of Large Language Models (LLMs) for production environments.
- Oversee the deployment of AI models using containerization (Docker/Kubernetes) and cloud services (AWS/GCP).
- Collaborate with data scientists and engineers to ensure seamless integration of AI capabilities into our products.
- Establish best practices for code quality, testing, and CI/CD pipelines within the AI team.
- Ensure data security, privacy, and compliance with industry standards (GDPR/CCPA).
- Conduct performance tuning and cost optimization for large-scale machine learning workloads.
Qualifications
- 10+ years of experience in software engineering and machine learning infrastructure.
- Deep expertise in Python, SQL, and modern machine learning frameworks.
- Strong proficiency in cloud computing platforms (AWS, GCP, or Azure).
- Experience with container orchestration (Kubernetes) and serverless architectures.
- Background in Natural Language Processing (NLP) and Generative AI.
- Excellent problem-solving skills and ability to thrive in a fast-paced, innovative environment.
- BS/MS in Computer Science, Engineering, or a related technical field.