Develops and maintains scalable AI infrastructure to support machine learning models and data pipelines. Requires expertise in cloud platforms, containerization, and ML frameworks.
Salary not listed
HybridML Engineering
About the role
Responsibilities
Build and maintain AI infrastructure systems.
Requirements
Nice-to-haves
Skills
PythonKubernetesTensorFlowPyTorchAWSDockerLinuxCI/CDMachine LearningDistributed Systems
Build and ship production AI agents on Cloudflare's edge platform using Workers, Durable Objects, and AI tools. Requires strong TypeScript/Rust experience, observability expertise, and hands-on LLM tooling for evals, safety, and multi-agent systems.
Salary not listed
On-siteML Engineering
CoDesign & NextGen Performance Engineer
Cerebras SystemsSunnyvale, CA
Characterize, analyze, and optimize performance of state-of-the-art AI models on Cerebras' wafer-scale hardware. Build performance models, optimize kernels and compilers, debug runtime behavior, and develop visualization tools to influence next-gen AI architecture.
Salary not listed
On-site3+ YOEML Engineering
Research Engineer, Privacy
OpenAISan Francisco, CA
Research Engineer on OpenAI's Privacy team designing and prototyping privacy-preserving ML algorithms like differential privacy and federated learning at scale. Requires hands-on PETs experience, fluency in PyTorch/JAX, and a track record implementing or publishing novel privacy work.
380k – 445k/yr
HybridML Engineering
Research Engineer
ConsoleSan Francisco, CA
Research Engineer building self-improving AI agent systems at Console. Develop eval/optimization loops, fine-tune specialist models, and improve agent reasoning over enterprise context using production data to drive measurable gains in quality, latency, and reliability.
200k – 350k/yr
On-siteML Engineering
Software Engineer, AI Platform
NotionSan Francisco, CA +1
Build and scale the shared AI platform foundations at Notion, enabling fast and safe shipping of AI products. Requires experience with LLM/ML platforms, strong ownership, and comfort across backend, infrastructure, and product code.