Job Description
Are you ready to shape the future of intelligent systems? 2026 is at the forefront of the artificial intelligence revolution, building the next generation of autonomous agents and neural architectures. We are looking for a visionary Senior AI Engineer to join our elite engineering team in San Francisco.
In this role, you won't just be writing code; you will be architecting the intelligence that will define the era of 2026 and beyond. We value radical innovation, technical excellence, and a deep commitment to ethical AI development. If you are driven by complexity and want to solve problems that have never been solved before, we want to meet you.
Why join 2026?
- Work on state-of-the-art Large Language Models and generative AI.
- Competitive equity package and top-tier compensation.
- Flexible remote-first culture with a collaborative hub in SF.
Responsibilities
- Design, train, and fine-tune large-scale machine learning models using PyTorch and TensorFlow.
- Collaborate with cross-functional teams of researchers and product managers to translate business requirements into technical solutions.
- Optimize inference pipelines to ensure low-latency, high-throughput performance in production environments.
- Conduct rigorous experimentation and A/B testing to validate model improvements and drive product growth.
- Mentor junior engineers and contribute to the technical roadmap of the AI department.
- Stay abreast of the latest advancements in NLP, Computer Vision, and Reinforcement Learning.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, or a related technical field.
- 5+ years of professional experience in machine learning, deep learning, or AI research.
- Strong proficiency in Python and experience with deep learning frameworks (PyTorch, TensorFlow, JAX).
- Proven track record of deploying scalable ML models to cloud environments (AWS, GCP, or Azure).
- Experience with MLOps tools such as MLflow, Kubeflow, or Docker.
- Excellent communication skills and the ability to explain complex technical concepts to non-technical stakeholders.