Job Description
Are you ready to architect the future of intelligent systems?
2026 is looking for a visionary Senior AI Architect to lead the next generation of our core technology stack. In this high-impact role, you will be at the forefront of innovation, designing scalable machine learning infrastructure that pushes the boundaries of what is possible. We are seeking a problem solver who thrives in a dynamic environment and is passionate about building robust, production-ready AI solutions.
Why Join 2026?
- Work on cutting-edge AI research and deployment.
- Competitive compensation package and equity options.
- Flexible remote-first culture with a collaborative office in San Francisco.
If you are ready to define the roadmap for artificial intelligence in the coming decade, we want to hear from you.
Responsibilities
- Design and architect scalable machine learning pipelines and infrastructure using cloud-native technologies (AWS, GCP, or Azure).
- Lead the end-to-end lifecycle of AI model development, from data ingestion and processing to training, evaluation, and deployment.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to translate business requirements into technical AI solutions.
- Optimize existing models for latency, throughput, and cost efficiency in high-volume production environments.
- Establish best practices, coding standards, and architectural guidelines for AI development within the organization.
- Stay abreast of the latest advancements in AI research and implement novel techniques to improve system performance.
Qualifications
- Master’s or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.
- Minimum of 6+ years of professional experience in software engineering and machine learning architecture.
- Strong proficiency in programming languages such as Python, Java, or C++.
- Deep experience with machine learning frameworks (TensorFlow, PyTorch, Scikit-learn) and model serving tools (Kubernetes, TorchServe, TensorFlow Serving).
- Extensive experience with cloud platforms and containerization technologies (Docker, Kubernetes).
- Proven track record of deploying large-scale AI systems that handle millions of requests per day.