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Slurm Jobs in Michigan (NOW HIRING)

Hands-on experience managing HPC clusters and job schedulers (LSF, Slurm, PBS, or similar). * Proven experience in CAE application support and integration. * Strong scripting skills (Bash, Shell ...

Data Architect Senior

Ann Arbor, MI · On-site

$65.75 - $88/hr

Experience with high-performance, distributed, or cloud computing; familiarity with SLURM is strongly valued. * Ability to work independently and collaborate across disciplines, with a strong ...

Showing results 21-40

Slurm information

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 their execution, monitoring, and scheduling. Knowledge of command-line tools and job scripts is essential for managing Slurm jobs effectively.
Infographic showing various Slurm job openings in Michigan as of July 2026, with employment types broken down into 99% Full Time, and 1% Contract. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution.

Machine Learning Engineer

Bespoke Labs

Lansing, MI

Full-time

Re-posted 23 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