Job Description
We are building the future. As a Senior AI Architect on our Project 2026 initiative, you will be at the forefront of defining the next generation of intelligent systems. We are looking for a visionary engineer who isn't just comfortable with the technology of today, but is driven to architect the breakthroughs of tomorrow.
In this role, you will lead the design and implementation of scalable, state-of-the-art machine learning models. You will collaborate with top-tier researchers and product engineers to solve complex problems and deliver AI solutions that have a tangible impact on millions of users globally. If you are passionate about the trajectory of artificial intelligence and want to shape the industry standard for 2026, we want to hear from you.
Why Join Us?
- Work on cutting-edge Generative AI and Autonomous Systems.
- Competitive compensation package and equity opportunities.
- Flexible remote-first culture with access to premium San Francisco amenities.
- Continuous learning budget and conference attendance.
Responsibilities
- Architect and deploy scalable machine learning pipelines for real-time inference.
- Lead the technical vision for our 2026 roadmap, ensuring robustness and scalability.
- Design and fine-tune large language models (LLMs) for specific enterprise applications.
- Collaborate with cross-functional teams to integrate AI solutions into core products.
- Optimize model performance and reduce latency in high-traffic environments.
- Mentor junior engineers and establish best practices for AI/ML development.
Qualifications
- PhD or Master’s degree in Computer Science, Artificial Intelligence, or a related field.
- 5+ years of professional experience in AI/ML engineering, with a focus on Deep Learning.
- Expert proficiency in Python, PyTorch, TensorFlow, and CUDA.
- Strong experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker/Kubernetes).
- Proven track record of delivering production-ready ML models at scale.
- Familiarity with ethical AI practices and bias mitigation in NLP models.