Machine Learning Engineer
Eugene, OR · On-site
... SLURM, or Ray) Solid understanding of evaluation methodology -- held-out sets, benchmark design, avoiding train/eval contamination
Machine Learning Engineer
Eugene, OR · On-site
... SLURM, or Ray) Solid understanding of evaluation methodology -- held-out sets, benchmark design, avoiding train/eval contamination
Machine Learning Engineer
Portland, OR · On-site
... SLURM, or Ray) Solid understanding of evaluation methodology -- held-out sets, benchmark design, avoiding train/eval contamination
Machine Learning Engineer
Portland, OR · On-site
... SLURM, or Ray) Solid understanding of evaluation methodology -- held-out sets, benchmark design, avoiding train/eval contamination
Machine Learning Engineer
Gresham, OR · On-site
... SLURM, or Ray) Solid understanding of evaluation methodology -- held-out sets, benchmark design, avoiding train/eval contamination
Machine Learning Engineer
Gresham, OR · On-site
... SLURM, or Ray) Solid understanding of evaluation methodology -- held-out sets, benchmark design, avoiding train/eval contamination
Machine Learning Engineer
Salem, OR · On-site
... SLURM, or Ray) Solid understanding of evaluation methodology -- held-out sets, benchmark design, avoiding train/eval contamination
Machine Learning Engineer
Salem, OR · On-site
... SLURM, or Ray) Solid understanding of evaluation methodology -- held-out sets, benchmark design, avoiding train/eval contamination
Experience running Slurm or custom scheduling frameworks in production ML environments. * Familiarity with GPU computing, Linux systems internals, and performance tuning at scale. Your base salary ...
Experience running Slurm or custom scheduling frameworks in production ML environments. * Familiarity with GPU computing, Linux systems internals, and performance tuning at scale. Your base salary ...
Senior Software Engineer - AI Research Clusters
$133K - $175K/yr
Experience running Slurm or custom scheduling frameworks in production ML environments. * Familiarity with GPU computing, Linux systems internals, and performance tuning at scale. Your base salary ...
Senior Software Engineer - AI Research Clusters
$133K - $175K/yr
Experience running Slurm or custom scheduling frameworks in production ML environments. * Familiarity with GPU computing, Linux systems internals, and performance tuning at scale. Your base salary ...
Senior Infrastructure and DevOps Engineer
Hillsboro, OR · On-site
$141K - $181K/yr
Experience with job scheduling systems (e.g., Slurm or similar). * Experience managing storage systems or distributed filesystems (e.g., NFS or similar). * Familiarity with performance tuning and ...
Senior Infrastructure and DevOps Engineer
Hillsboro, OR · On-site
$141K - $181K/yr
Experience with job scheduling systems (e.g., Slurm or similar). * Experience managing storage systems or distributed filesystems (e.g., NFS or similar). * Familiarity with performance tuning and ...
Slurm information
How to see Slurm jobs?
To see Slurm jobs, use the command 'squeue' to display queued and running jobs, or 'sacct' for accounting information on completed jobs. These commands help system administrators and users monitor job status in a high-performance computing environment. Proper permissions and environment modules are often required to access job details.
How many jobs can Slurm handle?
Slurm is a workload manager used in high-performance computing environments, capable of handling thousands to hundreds of thousands of jobs simultaneously depending on the system's hardware and configuration. Its scalability allows efficient scheduling and management of large job queues in supercomputing clusters. Proper system tuning and resource allocation are essential for optimal performance when managing large job volumes.
Is Slurm still used?
Slurm is a widely used open-source workload manager for high-performance computing clusters. It is actively maintained and commonly employed in research, scientific, and enterprise environments to schedule and manage jobs efficiently.
What is a Slurm job?
A Slurm job refers to a task or set of tasks submitted to a Slurm workload manager, which schedules and manages compute jobs on high-performance computing clusters. Users submit jobs with specific resource requirements, and Slurm handles job queuing, execution, and monitoring. Knowledge of command-line tools and job scripting is essential for managing Slurm jobs effectively.
What are popular job titles related to Slurm jobs in Oregon? For Slurm jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Slurm jobs in Oregon look for? The top searched job categories for Slurm jobs in Oregon are:
Full-time
Posted 28 days ago
Job description
About Us
We are AI researchers and builders who understand how to curate data and RL environments that truly improve models. We curated OpenThoughts, one of the best open reasoning datasets, and have trained SOTA models such as Bespoke-MiniCheck and Bespoke-MiniChart.
We are embarked on a journey to build Environments that are entire digital worlds that can be used to push the frontier of agents.
What You'll Be Working On
You will work directly with our research team on RL environment and task creation for agent training. This means designing observation spaces, action spaces, reward signals, and success criteria for new environments — and building the infrastructure that makes world-scale RL training possible. This is a high-ownership role; you will be building novel systems, not maintaining legacy ones.
Must-Have Skills
3+ years of ML engineering experience — model training, fine-tuning, or post-training pipelines in research or production
Strong Python and deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed precision)
Hands-on experience with LLM post-training — SFT, RLHF, PPO, DPO, or reward model training — and understanding of how training data quality affects model behavior
Familiarity with RL frameworks (Gymnasium, dm_env) and the ability to design or modify reward functions for agent training objectives
Experience running experiments at scale on cloud or HPC (AWS, GCP, SLURM, or Ray)
Solid understanding of evaluation methodology — held-out sets, benchmark design, avoiding train/eval contamination