Job Description
We are at the forefront of innovation, seeking a visionary Senior AI Architect to lead the development of next-generation artificial intelligence systems. In this pivotal role, you will define the technical roadmap for our projects, ensuring our solutions are scalable, secure, and ready for the demands of the year 2026 and beyond. You will work in a high-performance environment where cutting-edge research meets practical application.
Why Join Us?
- Work on projects that shape the future of automation and intelligence.
- Competitive compensation and equity package.
- Flexible remote-first policy with a premium office in downtown SF.
Responsibilities
- Architectural Leadership: Design and implement robust, scalable AI infrastructure and machine learning pipelines that align with 2026 technological standards.
- Model Development: Lead the research and development of advanced models, including Large Language Models (LLMs) and predictive analytics systems.
- System Optimization: Continuously monitor, optimize, and fine-tune model performance to ensure low latency and high accuracy in production environments.
- Collaboration: Partner with cross-functional teams of data scientists, engineers, and product managers to translate business requirements into technical solutions.
- Code Quality & Standards: Establish and enforce coding standards, conduct rigorous code reviews, and mentor junior engineers to foster a culture of excellence.
- Innovation: Stay abreast of emerging AI trends and research to integrate novel technologies into our product suite.
Qualifications
- Education: Master’s or PhD in Computer Science, Machine Learning, Mathematics, or a related field.
- Experience: 7+ years of professional experience in software engineering and machine learning, with at least 3 years in a senior or lead technical role.
- Programming: Deep expertise in Python and C++, with a strong understanding of software design patterns and best practices.
- Frameworks: Proficient in ML frameworks such as PyTorch, TensorFlow, or JAX.
- Cloud Infrastructure: Extensive experience deploying models on cloud platforms (AWS, GCP, or Azure) using containerization tools like Docker and Kubernetes.
- Problem Solving: Demonstrated ability to solve complex, unstructured problems and optimize high-scale systems.