Job Description
We are seeking a visionary Senior AI Infrastructure Engineer to architect the foundational systems for our 2026 roadmap. In this role, you will bridge the gap between cutting-edge machine learning research and scalable production environments. You will be responsible for building the robust, secure, and efficient infrastructure that powers our next-generation AI models. If you are passionate about the future of technology and want to define the standards for AI deployment in the coming years, we want to hear from you.
Why Join Us?
- Work on mission-critical projects that define the future of intelligent systems.
- Competitive compensation package and equity options.
- Flexible remote-first policy with access to top-tier amenities.
- Opportunity to work with industry leaders in AI and cloud computing.
Responsibilities
- Design, build, and maintain scalable AI infrastructure using Kubernetes, Docker, and serverless architectures.
- Optimize model inference latency and resource utilization for high-volume production workloads.
- Collaborate with data scientists to integrate MLOps pipelines that streamline the model lifecycle from training to deployment.
- Implement advanced security protocols and data governance frameworks to protect sensitive AI models.
- Drive architectural decisions that align with our 2026 technology roadmap and scalability goals.
- Mentor junior engineers and foster a culture of innovation and technical excellence.
Qualifications
- 7+ years of experience in software engineering, with a focus on machine learning infrastructure.
- Deep expertise in Python, C++, and modern cloud platforms (AWS, GCP, or Azure).
- Strong proficiency in containerization technologies (Docker, Kubernetes) and microservices architecture.
- Experience with MLOps tools (MLflow, Kubeflow) and CI/CD automation.
- Proven track record of deploying large-scale AI systems handling high concurrency.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.