Job Description
We are seeking a visionary Senior AI Infrastructure Engineer to lead the technical architecture for our upcoming 2026 roadmap. You will be at the forefront of deploying next-generation machine learning models, bridging the gap between cutting-edge research and production-grade infrastructure. If you are passionate about building scalable systems that power the future of AI, we want to hear from you.
Why Join Us?
- Work on projects that define the technological landscape of 2026.
- Competitive salary and equity package.
- Flexible remote and hybrid work options.
- Access to state-of-the-art hardware and cloud resources.
Responsibilities
- Architect and deploy scalable machine learning pipelines using Kubernetes and containerized environments.
- Optimize model inference latency and resource utilization for high-volume edge computing scenarios.
- Collaborate with research teams to translate theoretical models into robust, production-ready software.
- Implement and enforce security protocols for sensitive data and AI workloads.
- Design fault-tolerant systems capable of handling billions of data points daily.
- Conduct code reviews and mentor junior engineers on best practices in MLOps and cloud architecture.
Qualifications
- Bachelor’s degree in Computer Science, Engineering, or a related technical field (Master’s preferred).
- 5+ years of professional experience in backend engineering, DevOps, or MLOps.
- Deep proficiency in Python, TensorFlow, PyTorch, and C++.
- Extensive experience with cloud platforms (AWS, GCP, or Azure) and orchestration tools.
- Strong understanding of distributed systems, microservices, and message queues.
- Experience with data versioning tools like DVC and model registry platforms.