Job Description
Are you ready to architect the future of machine learning? 2026 Innovations is looking for a visionary Senior AI Infrastructure Engineer to join our elite engineering team in San Francisco. We are building the next generation of generative AI models and require an expert to ensure our infrastructure scales effortlessly.
As a key member of our technical staff, you will bridge the gap between cutting-edge research and production-grade systems. You will work in a fast-paced, collaborative environment where your code will power the AI experiences of millions. If you are passionate about optimizing deep learning pipelines and deploying robust systems at scale, we want to hear from you.
Why Join 2026 Innovations?
As a key member of our technical staff, you will bridge the gap between cutting-edge research and production-grade systems. You will work in a fast-paced, collaborative environment where your code will power the AI experiences of millions. If you are passionate about optimizing deep learning pipelines and deploying robust systems at scale, we want to hear from you.
Why Join 2026 Innovations?
- Work with state-of-the-art AI frameworks and hardware.
- Competitive compensation and equity packages.
- Flexible remote and hybrid work options.
- Continuous learning and professional development budget.
Responsibilities
- Design, build, and maintain scalable machine learning infrastructure pipelines for training and inference.
- Optimize model performance and resource utilization across heterogeneous hardware (GPUs/TPUs).
- Implement and advocate for CI/CD practices specifically tailored for ML workflows.
- Collaborate with data scientists and researchers to translate models into production services.
- Ensure high availability, fault tolerance, and observability of our AI systems.
- Conduct code reviews and mentor junior engineers to maintain high technical standards.
Qualifications
- BS, MS, or PhD in Computer Science, Electrical Engineering, or a related technical field.
- 5+ years of experience in software engineering, with at least 3 years focused on AI/ML infrastructure.
- Strong proficiency in Python, C++, and at least one deep learning framework (PyTorch or TensorFlow).
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Deep understanding of distributed systems, data structures, and algorithms.
- Experience with MLOps tools and production deployment strategies.