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Virtual Aws Machine Learning Jobs in Frisco, TX (NOW HIRING)

... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ... HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology -- held-out sets ...

Principal Machine Learning Scientist

Dallas, TX · On-site

  • Medical

  • Life

  • Retirement

  • PTO

The Principal Machine Learning Scientist will design, develop, and deliver Machine Learning based ... AWS, GCP), cloud-based sandbox environment and analytics sandbox and libraries. * Ability to work ...

AI/ML Architect with Databricks , AWS Remote Role Overview We are seeking an experienced AI/ML ... machine learning platforms. The ideal candidate combines architectural thinking with strong ...

Lead Machine Learning Engineer

Plano, TX · On-site

$98K - $129K/yr

Lead Machine Learning Engineer As a Capital One Lead Machine Learning Engineer (MLE), you'll be ... Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google ...

Lead Machine Learning Engineer

Plano, TX · On-site

$98K - $129K/yr

Lead Machine Learning Engineer As a Capital One Lead Machine Learning Engineer (MLE), you'll be ... Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google ...

AI/ML Architect with Databricks, AWS Location: Los Angeles, CA (Hybrid) Hire type: FTE / CTH Role ... machine learning platforms. The ideal candidate combines architectural thinking with strong ...

Principal Machine Learning Scientist

Dallas, TX · Remote

  • Medical

  • Life

  • Retirement

  • PTO

The Principal Machine Learning Scientist will design, develop, and deliverMachine ... AWS, GCP), cloud-based sandbox environment and analytics sandbox and libraries. * Ability to work ...

Machine Learning Operations Engineer

Dallas, TX · On-site

$68K - $93K/yr

Machine Learning Operations Engineer Location: Dallas, Texas Type: Contract To Hire Visa : USC, GC ... Work with AWS and SageMaker MLOps ecosystem. Requirements * 6+ years of experience in software ...

Machine Learning Operations Engineer

Dallas, TX · On-site

$68K - $93K/yr

Machine Learning Operations Engineer Location: Dallas, Texas Type: Contract To Hire Visa : USC, GC ... Work with AWS and SageMaker MLOps ecosystem. Requirements * 6+ years of experience in software ...

Machine Learning Operations Engineer

Dallas, TX · On-site

$68K - $93K/yr

Machine Learning Operations Engineer Location: Dallas, Texas Type: Contract To Hire Visa : USC, GC ... Work with AWS and SageMaker MLOps ecosystem. Requirements * 6+ years of experience in software ...

Showing results 21-40

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Machine Learning Engineer

Bespoke Labs

Mckinney, TX • On-site

Full-time

Re-posted 29 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