Cloud Machine Learning Engineer
Core
Design, build, and deploy scalable machine learning solutions leveraging cloud technologies to deliver performant, secure, and user-friendly APIs and developer experiences.
Role type
Cloud Machine Learning Engineer
Builds
Production ML systems, developer APIs, and MLOps pipelines
Domain
Cloud infrastructure and Machine Learning
Deliverable
production ML models | product features | infrastructure
Required skills
Deep learning frameworks (PyTorch), ML libraries (Transformers, Diffusers, Accelerate, Datasets), Cloud platforms (AWS, Azure, GCP), MLOps pipelines, Containerization (Docker), Orchestration (Kubernetes), Python, Technical documentation
Preferred skills
TypeScript, Rust, MongoDB, Front-end frameworks (Svelte, TailwindCSS), Open-source ML community contributions, XLA, hardware accelerators, distributed training techniques
Technologies
PyTorch, Transformers, Diffusers, Accelerate, Datasets, AWS, Azure, GCP, SageMaker, EC2, S3, Docker, Kubernetes, Python, TypeScript, Rust, MongoDB, Svelte, TailwindCSS
Responsibilities
Integrate machine learning models with cloud platforms and managed SaaS solutions; Ensure deployed ML models meet performance, reliability, and scalability requirements; Design, develop, and maintain secure and user-friendly developer APIs and interfaces; Build and optimize MLOps pipelines, including containerization with Docker and orchestration with Kubernetes; Write technical documentation, tutorials, and examples to support internal teams and external users; Collaborate with cross-functional teams to align development efforts with strategic goals
Seniority
Mid-to-Senior, hands-on IC