Job Description
Are you ready to shape the future of Artificial Intelligence?
At 2026, we are building the technological foundation for tomorrow. We are looking for a visionary Senior AI Engineer to join our elite team in San Francisco. You will be at the forefront of developing next-generation machine learning models that solve complex, real-world problems. If you are passionate about pushing the boundaries of what AI can achieve and want to work in a high-growth environment, we want to hear from you.
Join us in defining the next era of intelligent systems.
At 2026, we are building the technological foundation for tomorrow. We are looking for a visionary Senior AI Engineer to join our elite team in San Francisco. You will be at the forefront of developing next-generation machine learning models that solve complex, real-world problems. If you are passionate about pushing the boundaries of what AI can achieve and want to work in a high-growth environment, we want to hear from you.
Join us in defining the next era of intelligent systems.
Responsibilities
- Design, develop, and deploy scalable machine learning pipelines and models using Python, TensorFlow, and PyTorch.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to translate business requirements into technical solutions.
- Optimize existing algorithms for speed, accuracy, and efficiency, ensuring high performance in production environments.
- Conduct rigorous testing, validation, and documentation of models to ensure reliability and regulatory compliance.
- Mentor junior engineers and provide technical leadership within the AI research group.
- Stay abreast of the latest advancements in AI/ML research and integrate cutting-edge methodologies into our stack.
Qualifications
- Master’s degree or PhD in Computer Science, Statistics, Mathematics, or a related field.
- 5+ years of professional experience in machine learning engineering or a related technical role.
- Strong proficiency in Python and deep learning frameworks (TensorFlow, PyTorch, JAX).
- Extensive experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Proven track record of deploying end-to-end ML systems to production.
- Experience with NLP, Computer Vision, or Reinforcement Learning is a strong plus.