We build Industrial AI for the world's leading manufacturers for real production data with real yield impact. We are currently building our own tabular foundation models (pretraining, fine-tuning, serving at scale) and Transformer architectures for time-series forecasting on noisy, sparse, irregularly sampled sensor data.
Senior AI Engineer - ML (Palo Alto): own the training/serving/monitoring infrastructure for our foundation models and take them from prototype to production. Python, PyTorch, Docker/K8s, CI/CD; 3+ yrs production ML infra; BS+6 or MS/PhD+4. Distributed multi-GPU training a plus. https://jobs.lever.co/gausslabs/13bb4715-22f7-40a7-a941-4612...
AI Scientist - ML (Palo Alto or Seoul): design Transformer-based sequence models for manufacturing time series, own EDA through deployment, publish and patent. MS/PhD, 3+ yrs deep learning on time series, PyTorch, top-tier pubs. https://jobs.lever.co/gausslabs/dbfd0b6c-d2e9-460c-91a0-6dde...
Stanford Research Computing (https://srcc.stanford.edu) is a collaboration between University IT and the Vice Provost and Dean of Research. We operate HPC environments for researchers, we do one-time consultations on projects (from software and pipelines, to data management, to physical building design and fit-out), and we provide contract support for individual Labs, Departments, and Schools.
We have four open positions, three hybrid and one (marked) onsite:
• Principal Storage Architect & Team Lead: Our current storage team lead is moving on to Industry, so we're splitting his work into two separate roles. This is the Technical Manager position: You'll be leading the storage team, setting the direction for our large storage environments: Oak (file storage, used by multiple cluster), Fir (fast scratch for Sherlock), and Elm (object storage on top of tape). Knowledge of Lustre, Infiniband, and PB-scale storage is important. More info: https://bit.ly/44PbQnr
• Storage Architect or Storage Sysadmin: This is the second role I referenced above. You'll be maintaining & expanding Oak, our 20+ Pebibyte Lustre storage environment used by our largest HPC clusters. Depending on your experience level, you might also have some responsibility for Elm, which provides object storage on top of tape. Knowledge of Lustre, Infiniband, and PB-scale storage is important here, too. More info: https://bit.ly/4y8lj6R
• GPU System Engineer: We are looking to hire a lead sysadmin for Marlowe—our 1SU NVIDIA DGX H100 SuperPOD with DDN Intelliflash and DDN NFS storage—launched. You'll be working with the latest AI/ML/Deep Learning/LLM software & frameworks, getting them to work in an HPC environment. You'll be keeping the environment up-to-date, and working with NVIDIA/DDN when there's trouble. You should also expect to interact with users & PIs a lot. More info: https://bit.ly/4vf7aly
• HPC Hardware & Infra Sysadmin [ONSITE]: We are looking for a system administrator to help run the hardware & infrastructure portions of Sherlock, our largest HPC cluster. Sherlock is a mix of Intel & AMD x86_64 servers, with three Infiniband fabrics, plus an Ethernet backbone. You'll be responsible for maintaining, troubleshooting, and improving the hardware of Sherlock. That is, keeping things working, and figuring out how to make it better. More info: https://bit.ly/3SPRpnJ
If you don't already live in the Bay Area, we provide a relocation incentive. Depending on where you live, we provide free transit passes. Unfortunately, if you drive, you will have to pay for parking for the days you're on-site. There is some on-call around the holidays. We get a 403(b) match, good healthcare, and 30+ days off per year (holidays + vacation). All Benefits are all publicly documented at https://cardinalatwork.stanford.edu/benefits-rewards.
If you have questions, feel free to reply here or email me (the info is in my profile)!