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Weekend Machine Learning Jobs in Virginia (NOW HIRING)

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 ...

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 ...

Overview SOSi is seeking a skilled Machine Learning Engineer to support a US government customer in Chantilly, VA. In this job you will work with other talented data scientists, software developers ...

Machine Learning Engineer- Senior

Chantilly, VA · On-site

$125K - $165K/yr

Overview SOSi is seeking a skilled Machine Learning Engineer to support a US government customer in Chantilly, VA. In this job you will work with other talented data scientists, software developers ...

Machine Learning Engineer - Remote

Vienna, VA · On-site +1

$140K - $150K/yr

Halvik is a highly successful WOB business with more than 50 prime contracts and 500+ professionals delivering Digital Services, Advanced Analytics, Artificial Intelligence/Machine Learning ...

Halvik is a highly successful WOB business with more than 50 prime contracts and 500+ professionals delivering Digital Services, Advanced Analytics, Artificial Intelligence/Machine Learning ...

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Weekend Machine Learning information

What are the most commonly searched types of Machine Learning jobs in Virginia? The most popular types of Machine Learning jobs in Virginia are:
What cities in Virginia are hiring for Weekend Machine Learning jobs? Cities in Virginia with the most Weekend Machine Learning job openings:

Machine Learning Engineer

Bespoke Labs

Norfolk, VA • On-site

Full-time

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