Job Description
About 2026
We are the architects of the next decade of intelligent systems. At 2026, we don't just predict the future; we build the infrastructure that makes it possible. Our mission is to revolutionize how enterprises leverage predictive AI through scalable, secure, and transparent machine learning models. We are looking for a visionary Senior AI Engineer to join our elite engineering team in San Francisco.
The Role
In this pivotal role, you will bridge the gap between theoretical research and production-grade engineering. You will lead the development of our core inference engines, optimize large-scale neural networks, and mentor junior engineers to uphold our high standards of technical excellence.
Responsibilities
- Lead Architecture: Design and implement scalable machine learning infrastructure that can handle petabyte-scale data ingestion and real-time inference.
- Model Optimization: Apply advanced quantization, pruning, and distillation techniques to reduce latency and improve model efficiency on edge devices.
- Research & Dev: Experiment with cutting-edge LLM architectures and proprietary algorithms to push the boundaries of our product capabilities.
- Code Quality: Write clean, maintainable, and well-documented code while establishing rigorous CI/CD pipelines for automated testing and deployment.
- Collaboration: Partner with data scientists and product managers to translate complex business requirements into robust technical solutions.
- Mentorship: Guide the technical growth of the engineering team, conducting code reviews and fostering a culture of continuous learning.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Machine Learning, or a related quantitative field.
- Experience: 5+ years of professional experience in building production-grade AI/ML systems, with at least 2 years in a senior leadership role.
- Technical Stack: Deep expertise in Python, PyTorch, or TensorFlow. Proficiency in cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Problem Solving: Proven track record of solving complex performance bottlenecks in large-scale distributed systems.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders and cross-functional teams.
- Tools: Strong command of Git, CI/CD tools (Jenkins, GitHub Actions), and monitoring/logging systems (Prometheus, Grafana, ELK).