Job Description
Are you ready to engineer the future? At 2026 Dynamics, we aren't just predicting the future; we are building it. We are a cutting-edge AI research lab focused on next-generation generative models and autonomous systems. We are looking for a visionary Senior AI Engineer to join our elite team in San Francisco.
We are seeking a technical mastermind who thrives on complexity and wants to define the trajectory of artificial intelligence. In this role, you will bridge the gap between theoretical research and production-grade systems, directly impacting millions of users worldwide.
Why Join Us?
- Work on the bleeding edge of Generative AI and Large Language Models (LLMs).
- Competitive compensation package with equity options.
- Flexible remote-first culture with a state-of-the-art office in downtown SF.
- Continuous learning budget and access to the latest tech stacks.
Core Responsibilities
- Design, train, and deploy scalable machine learning models for high-traffic applications.
- Lead the architecture and optimization of deep learning pipelines and data infrastructure.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to translate research into market-ready products.
- Mentor junior engineers, conducting code reviews and technical architecture planning.
- Stay abreast of the latest advancements in NLP, Computer Vision, and Reinforcement Learning to drive innovation.
Qualifications
- Master’s or Ph.D. degree in Computer Science, Artificial Intelligence, or a related quantitative field.
- 5+ years of professional experience in software engineering and machine learning.
- Expert proficiency in Python, TensorFlow, PyTorch, or JAX.
- Strong understanding of distributed systems and cloud computing platforms (AWS, GCP, or Azure).
- Experience with MLOps tools such as Docker, Kubernetes, and MLflow.
Responsibilities
- Design, train, and deploy scalable machine learning models for high-traffic applications.
- Lead the architecture and optimization of deep learning pipelines and data infrastructure.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to translate research into market-ready products.
- Mentor junior engineers, conducting code reviews and technical architecture planning.
- Stay abreast of the latest advancements in NLP, Computer Vision, and Reinforcement Learning to drive innovation.
Qualifications
- Master’s or Ph.D. degree in Computer Science, Artificial Intelligence, or a related quantitative field.
- 5+ years of professional experience in software engineering and machine learning.
- Expert proficiency in Python, TensorFlow, PyTorch, or JAX.
- Strong understanding of distributed systems and cloud computing platforms (AWS, GCP, or Azure).
- Experience with MLOps tools such as Docker, Kubernetes, and MLflow.