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Hpc Aws Jobs (NOW HIRING)

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Hpc Aws information

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$11

$54

$77

How much do hpc aws jobs pay per hour?

As of Aug 6, 2026, the average hourly pay for hpc aws in the United States is $54.05, according to ZipRecruiter salary data. Most workers in this role earn between $38.70 and $64.42 per hour, depending on experience, location, and employer.

What is the difference between Hpc Aws vs Cloud Computing Engineer?

AspectHpc AwsCloud Computing Engineer
Required CredentialsAWS certifications, HPC knowledgeCloud certifications, software development skills
Work EnvironmentHigh-performance computing clusters on AWSVarious cloud platforms, software deployment
Employer & IndustryResearch institutions, tech companies using HPC on AWSTech firms, startups, enterprises using cloud solutions
Search & Comparison IntentFocus on HPC-specific AWS rolesBroader cloud roles, less HPC-specific

Hpc Aws professionals specialize in managing high-performance computing workloads on AWS, often requiring HPC and AWS certifications. In contrast, Cloud Computing Engineers have a broader focus on cloud infrastructure and software deployment across various platforms. While both roles work within cloud environments, Hpc Aws roles are more specialized in HPC on AWS, whereas Cloud Computing Engineers handle general cloud solutions.

More about Hpc Aws jobs
What cities are hiring for Hpc Aws jobs? Cities with the most Hpc Aws job openings:
What states have the most Hpc Aws jobs? States with the most job openings for Hpc Aws jobs include:
Infographic showing various Hpc Aws job openings in the United States as of August 2026, with employment types broken down into 89% Full Time, 1% Part Time, and 10% Contract. Highlights an 81% Physical, 5% Hybrid, and 14% Remote job distribution, with an average salary of $112,422 per year, or $54 per hour.

Machine Learning Engineer

Bespoke Labs

Minneapolis, MN • On-site

Full-time

Re-posted 20 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