Job Description
Are you ready to define the future of technology? 2026 is at the forefront of the AI revolution, building next-generation generative models that transcend current industry standards. We are looking for a visionary Senior AI Research Engineer to join our elite team in San Francisco. In this role, you won't just implement existing algorithms; you will pioneer new methodologies that solve complex, unsolved problems in machine learning and neural architecture.
At 2026, we believe in a culture of radical transparency, continuous learning, and high-impact execution. You will have the autonomy to experiment, the resources to scale, and the mentorship to grow into a leadership role in one of the most exciting tech sectors of the decade.
Why join 2026?
- Work on projects that will impact billions of users globally.
- Competitive equity package and top-tier compensation.
- State-of-the-art computing infrastructure and research grants.
Responsibilities
- Lead the design, development, and deployment of state-of-the-art deep learning models and neural networks.
- Conduct cutting-edge research to improve model efficiency, accuracy, and generalization capabilities.
- Collaborate with cross-functional teams of engineers, data scientists, and product managers to translate research into scalable production systems.
- Optimize existing pipelines for high-throughput inference and low-latency performance.
- Publish high-impact research papers and contribute to open-source communities to establish 2026 as a thought leader in the industry.
- Mentor junior engineers and researchers, fostering a culture of innovation and technical excellence.
Qualifications
- PhD in Computer Science, Mathematics, or a related technical field (or equivalent practical experience).
- 5+ years of professional experience in machine learning, deep learning, or artificial intelligence research.
- Extensive experience with Python, PyTorch, TensorFlow, or JAX.
- Strong proficiency in Natural Language Processing (NLP) or Computer Vision, with a preference for Generative AI experience.
- Proven track record of publishing in top-tier conferences (NeurIPS, ICML, ICLR, ACL, CVPR).
- Experience deploying models to production environments (e.g., AWS, GCP, Azure, Kubernetes).
- Strong problem-solving skills and the ability to thrive in a fast-paced, ambiguous startup environment.