Job Description
Are you ready to define the technological landscape of the future? 2026 Systems is seeking a visionary Senior Artificial Intelligence Engineer to join our elite team in San Francisco. We are building the next generation of autonomous agents and neural networks that will power the industries of tomorrow.
In this role, you will bridge the gap between theoretical research and production-grade deployment. You will work on complex algorithms that push the boundaries of what is possible, ensuring our systems are scalable, secure, and groundbreaking.
Why Join 2026 Systems?
- Work on cutting-edge projects that define the future of AI.
- Competitive compensation and equity packages.
- Top-tier talent and collaborative environment.
Responsibilities
- Design & Deploy: Architect and implement scalable machine learning models and deep learning frameworks for autonomous systems.
- Research: Stay at the forefront of AI advancements, researching novel architectures and optimization techniques.
- Infrastructure: Manage the end-to-end MLOps pipeline, including data ingestion, model training, and deployment to cloud environments.
- Coding: Write clean, efficient, and maintainable Python code, contributing to the core library of 2026 Systems.
- Mentorship: Guide junior engineers and data scientists, fostering a culture of technical excellence and innovation.
- Collaboration: Partner with product and engineering teams to translate business requirements into technical solutions.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- Experience: 5+ years of professional experience in AI/ML engineering, with a strong portfolio of deployed models.
- Technical Skills: Proficiency in Python (PyTorch, TensorFlow), SQL, and cloud platforms (AWS, GCP, or Azure).
- Problem Solving: Exceptional ability to solve complex mathematical and algorithmic problems.
- Communication: Strong verbal and written communication skills, capable of presenting complex technical concepts to non-technical stakeholders.