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What You’ll Do:
- Build & Scale AI Infrastructure: Design, implement, and maintain high-performance ML training and inference platforms.
- Develop MLOps Tools: Ship tools that allow any ML engineer to deploy a model in minutes, not days.
- Optimize Performance: Improve scalability, reliability, and cost efficiency of model training and serving systems.
Experience:
- 3+ years in Software Engineering or ML Platform/Infrastructure roles, with a focus on distributed systems, cloud services, or MLOps.
- Strong knowledge of cloud platforms (AWS, GCP, or Azure) and infrastructure-as-code tools (Terraform, CloudFormation).
- Experience with ML frameworks (TensorFlow, PyTorch, or similar) and orchestration tools (Kubeflow, Airflow, MLflow).
What we offer:
- A dynamic environment where your contributions shape the company and its products
- A team that values innovation, intuition, and drive
- Autonomy, fostering focus and creativity
Speechify
Speechify's mission is to make sure that reading is never a barrier to learning. With nearly 200 people around the globe working in a 100% distributed setting, Speechify's team includes frontend and backend engineers, AI research scientists, and others.