Machine Learning Infrastructure Engineer
Designs, builds, and maintains ML training and serving infrastructure, providing support to research teams. Requires 4+ years in ML infrastructure, cloud platforms like Kubernetes and Google Cloud, and GPU experience.
About the job
Responsibilities
- Provide infrastructure support to our ML research and product
- Build tooling to diagnose cluster issues and hardware failures
- Monitor deployments, manage experiments, and generally support our research
- Maximize GPU allocation and utilization for both serving and training
Requirements
- 4+ years of experience supporting the infrastructure within an ML environment
- Experience in developing tools used to diagnose ML infrastructure problems and failures
- Experience with cloud platforms (e.g., Compute Engine, Kubernetes, Cloud Storage)
- Experience working with GPUs
Nice to Have
- Experience with large GPU clusters and high-performance computing/networking
- Experience with supporting large language model training
- Experience with ML frameworks like Pytorch/TensorFlow/JAX
- Experience with GPU kernel development
Skills
Kubernetes, GCP, Compute Engine, Cloud Storage, Gpus, PyTorch, TensorFlow, JAX, Gpu Kernel Development, Large Gpu Clusters
Similar jobs
ML Engineering jobs
LangChain
New York, NYBuild and teach reliable AI agent systems through customer workshops, technical content, guidance, and reference implementations. The role requires strong Python and agent-development experience plus a background delivering customer-facing technical training.
Roboflow
San Francisco, CA
Build reinforcement-learning environments, evaluations, datasets, and scalable infrastructure for frontier AI capabilities. The role suits a high-agency generalist engineer with experience in agents, evaluations, or RL workflows and strong communication skills.
Beacon Biosignals
Boston, MADevelop and productionize machine- and deep-learning algorithms for biosignal and EEG data used in medical devices, clinical development, and diagnostics. The role requires 4+ years of industry experience, DSP and statistics expertise, PyTorch proficiency, and familiarity with regulated environments and production ML practices.
Applied Intuition
Sunnyvale, CA
Develop and deploy ML-first behavior prediction and planning systems for autonomous vehicles, forecasting the motion and interactions of road users. Requires a bachelor's degree, deep learning lifecycle expertise, and at least three years of production software experience with C++ or Python.
Fab2
Austin, TXBuild the AI platform behind fab2, including model infrastructure, agent systems, evaluations, and tools for engineering and fab operations. The role requires strong production software engineering skills and comfort working across frontend, backend, infrastructure, and data.