Job Description
We are seeking a visionary Senior AI Engineer to join 2026 Labs in San Francisco. As we stand on the precipice of the next technological revolution, our mission is to define the standards for artificial intelligence in the year 2026 and beyond. You will work at the intersection of cutting-edge research and scalable production engineering, leading a team of elite data scientists to build systems that anticipate user needs before they are even expressed.
In this pivotal role, you will own the technical architecture for our flagship product suite, ensuring our AI models are not only accurate but also ethical, efficient, and future-proof. We offer a competitive salary, equity package, and a culture that prioritizes innovation and autonomy.
Responsibilities
- Architect and deploy state-of-the-art machine learning models for large-scale production environments.
- Lead the research and development of novel algorithms to solve complex, unstructured problems.
- Collaborate with product managers to translate business requirements into technical specifications.
- Mentor junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
- Optimize model latency and throughput to ensure real-time performance across all platforms.
- Ensure data privacy, security, and compliance with industry regulations.
- Stay ahead of the curve on emerging AI trends and integrate relevant advancements into our tech stack.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, or a related field.
- 5+ years of professional experience in machine learning, deep learning, or natural language processing.
- Strong proficiency in Python, PyTorch, or TensorFlow.
- Proven track record of deploying models at scale in cloud environments (AWS, GCP, or Azure).
- Experience with MLOps tools and pipelines (Kubernetes, Docker, MLflow).
- Excellent problem-solving skills and ability to work in a fast-paced, agile environment.
- Strong communication skills and the ability to present technical concepts to non-technical stakeholders.